By 2028, 73% of all workgroups are expected to have virtual employees. The number of jobs that can be done from home is rising, and this is also happening in the UX (user experience) career path.

If you want to work as a UX designer without having a desk, this article features our best tips for getting ready. These suggestions should enable you to make a big change in your life with complete confidence in successful UI/UX design services.

10 Smart Tips to Start Working as a Remote UX Designer in 2024

If you would like to build your career as a remote UX designer, there are several things you need to keep in mind. Let’s go through the most important approaches for now.

1. Do your research: Is a remote job the right fit for you?

UX designers operate as touchpoints for partners, developers, and users. Daily tasks include interviewing people and conducting workshops.

Considering UX’s collaborative nature, you could wonder: Can a UX designer find remote work? Absolutely! UX design is an emerging remote field.

A rising number of firms are embracing a dynamic approach, allowing staffers to work from home at least part of every week. The UX market is packed with remote jobs and it will only grow in the future.

Remote UX designers have plenty of chances, but which companies hire them? Well, they can land a job in banking, tech, the auto industry, healthcare, eCommerce, and software.

You can operate remotely as web designers, freelance designers, internet analysts, online and internet marketing directors, customer success managers, and UX researchers.

By now, you have realized that the remote UX design job market is developing. Virtual UX designers even earn similar salaries as compared to in-house designers, based on company locations and experience levels.

Even as a novice or prospective UX designer, you may prefer to work remotely from the start. It’s true that with expertise, it’s simpler to get remote jobs easily.

Young designers may discover fewer remote employment options than experienced UXers because firms generally instruct novice designers in-house.

Well, if you can’t find a proper remote job right away, you can build experience by freelancing or offering your creative abilities to non-profits.

You may need to establish yourself before getting into a remote profession, but it’s feasible. So, this brings us to the next point.

2. Enhance your portfolio by showcasing UX research skills

It’s very important that the UX design profile is up to the mark, whether you’re searching for a career in-house or from home.

Via your portfolio, you’ll demonstrate before businesses not just what you’re good at, but also what you’re enthusiastic about in the world of design.

Be aware of the recent web design trends and showcase them on your profile to impress potential employers. Finally, is your portfolio ready? Ask yourself this question before starting to apply for jobs.

3. Showcase your knowledge of UX testing tools on your portfolio

For any UX designer, it is essential to have a comprehensive understanding of the prevalent UX testing tools and highlight them on his/her profile.

Some of these tools are guerilla testing, lab usability testing, unmoderated remote usability testing, contextual inquiry, and card sorting.

Another UX testing type is tree testing. Per this guide on UX research, it is a popular type of tool that lets you look at how topics are organized and how easy they are to find on a site or app.

Respondents in the test are given a text-only file of the website’s hierarchy and requested to do a set of exercises. The final objective is to address the question, “Can customers locate the information they are searching for?”

It’s an essential part of your plan for doing research.

4. Learn about the processes and tools for working remotely

First, you should consider how you will adjust your theory and practice in the virtual space. 

Understandably, there are a bunch of wonderful tools for UX design, but how would you change your method for working remotely?

How would you find out what users want and check how easy it is to use? 

How would you make sure you can talk freely with major stakeholders when you don’t see them in person?

Start by getting to know the tools which will make it feasible to work from home, like Zoom for conferences, HotJar for customer research, and so on.  

When applying for a job that lets you work from home, it’s necessary to highlight that you’ve considered what it’s like to work from home on a regular schedule and also how you’ll deal with several difficulties associated with it. 

Getting a great set of tools that can be used from a distance and doing your research are great starting points.

5. Know where to look for remote UX  job openings

If you are actively looking out, there are career boards that only list jobs, which can be done from home. 

Following the COVID-19 pandemic, several job portals have come up – that are revolutionizing how remote job-seekers find work. Such organizations understand the issues remote job-searchers confront.

With commitment and dedication to assist you in finding a safe, reputable remote UX designer position, such businesses are devoted to telecommuting success.

They can help you find a job by easing your quest while showcasing your knowledge and history before employers.

Multiple reputed remote job-search sites offer resources and tools – alongside supplemental support, a portal with unlimited postings, and career assistance. A relationship with such an agency can help you achieve your UX design goals.

6. Prepare for your interview

Writing a résumé and covering letter for a remote UX job is different from looking for an in-house UX job. Optimize it for virtual work.

Add remote talents to both your cover letter and resume. Use appropriate keywords in your documents that showcase your remote skills.

Now, once you are shortlisted, you need to prepare for your interview. Remember to discuss digital working methods and remote environments throughout the interview.

Keep your laptop ready, and ensure that you have fast and reliable internet. After all, dropped calls are the worst. A decent headphone with microphones reduces background sound. 

Set up your web camera and keep your background free of any clutter. Having mounds of clothes or rubbish in the video’s window reflects badly on you.

7. Improve your ability to communicate with people

To do well in a remote work situation, communication is a fundamental skill you have to learn. To design is to communicate in any way you can manage or master.

A UX designer’s performance relies on how efficiently s/he can explain design choices to people who aren’t designers. 

Professional communication is needed at each stage of the procedure to: 

• Get stakeholders on board with your strategy
• Narrate an interesting story about the customer lifecycle
• Clarify design deadlines in a logical manner
• Assist developers to recognize patterns of interaction and specifications of layouts

Owing to the unavailability of face-to-face engagement, it is much more important to communicate well when working from home. Our recommendation would be to never assume anything about the audience and always use multiple ways to talk to them.

When you hand over prototypes, notate them and use motion tools to show how interactions work. Try recording a video tour to ensure that the layout is clear.

8. Prep up yourself after landing a remote UX designer job

One of the best things about working from home is that you can set your hours and pace. No designer wants to be controlled to the last detail, because it kills their creativity. 

However, when you can work wherever and whenever you want, it takes an incredible amount of self-discipline to keep track of time.

You can give your customers a minute-by-minute summary of your billable hours, but time management isn’t just about being honest. 

It is about how well things work. At its finest, working from home gives you the chance to do deep work without interruptions, which might result in personal advancements that double your output.

But how can you designate long hours to difficult tasks without getting distracted? Plan your schedule in a manner that keeps you from getting distracted so that you can immerse yourself in deep working.

The Pomodoro technique, checking emails two times per day, and working offline between discussions are all simple tips, which can help you.

9. Master UX tools and strategies

Leverage the power of remote project tools and strategies, which include:

• Analytics reviews: Analyzing and recommending web and mobile utilization data.

• Online surveys: Creating an online questionnaire to gather user input.

• Competitor analysis: Auditing/reviewing competing sites and applications, user testing, generating competitor analysis reports.

• Heuristic evaluation: Assessing a web page for usability issues and other improvements.

• Content audit: Cataloging a client’s current content.

• Contextual inquiry: Interviewing people where they are using the website/app to know their jobs and challenges.

• Usability testing: Encouraging consumers to undertake activities and express their views.

• User profiles: Creating personas for your projects, combining primary and secondary data from analytics, polls, conversations, user testing activities, and other ongoing research. These profiles have names, photos, objectives, aspirations, and realistic backstories based on genuine site or app users.

• Scenarios: They describe one day in the regular life of a persona. Scenarios narrate how your product will help them in their lifestyle. 

• Mental models: Such frameworks depict scenarios visually. The technique uses a timeframe to portray moments in a participant’s life and adds a layer to your site or application’s functionalities that relate to each incident.

• Experience maps: Expanded mental models. They are zoomed-out, comprehensive visual pictures of users’ experiences with your business. Since many companies and initiatives are enormous and complicated, experience maps are frequently portrayed on a wide canvas.

• Storyboards: Filmmaking-inspired tool that captures a user’s experiences with products visually.

• Wireframes: These are roadmaps for an app or a website’s layout.

10. Practice self-care to avoid burnout

Even though working together with peers in an office doesn’t always mean you’re close emotionally, virtual workstations aren’t precisely the place to discover solid personal ties.

People are less involved, and it’s difficult to fix problems. Without regular contact with other people, it’s easy to lose motivation and engagement. 

You may get caught up in a loop of loneliness and isolation, which is bad for you physically and mentally in the long term.

Therefore, take additional care of your health. Take short breaks and get up and move around every so often. 

Find time for simple exercises you can do at home. And also don’t forget to take care of your mental health: talk to as many people as you can. Occasionally, a side project helps people get to know each other better. 

Most notably, try to stop thinking about work and focus on your living style. Working from home, where you are always on, can make it hard to tell the difference between life and work. At the close of the day, we don’t work to live, but rather live to work. 

Where to Look for Remote Work as a UX Designer

It’s easier than ever to find remote work from a UX designer in 2024. Here are some top platforms and resources to help you get started:

Toptal

This platform connects UX designers with top global clients, including Fortune 500 companies and startups. With Toptal, each client and job opportunity is vetted so you work with reputable companies. You can work whenever you want because work hours are flexible, and you can set your own rates.

Remote.co

There are many remote UI/UX design jobs available on remote.co. There are full time, full time, freelance, and work from ANYWHERE options. Webflow, Xometry and Hashicorp typically post job opening here.

FlexJobs

FlexJobs provides a curated list of remote UX designer jobs. You can find entry level, manager and director level job opportunities. In addition, they offer flexible schedules and a multitude of different kinds of jobs.

Working Nomads

Fully remote UX jobs anywhere in the world are available on Working Nomads. This is where you can apply for UX Designer, User Experience Researcher and Interaction Designer positions.

Conclusion

More and more UX designers are working remotely in 2024. At the moment, roughly 22% of the US workforce are working remotely, and that number is predicted to rise. Work location flexibility is a fast emerging trend, with 67% of companies offering this flexibility, including us here at Designveloper. This shift has given not just UX designers but web developers and many others the opportunity to work from wherever in the globe.

For example, you might be a UX designer in Tokyo and the development team you work with is in San Francisco — suddenly you don’t even need to be in the same physical place. This flexibility not only improves work life balance, but will also foster a more diverse and inclusive workforce. According to Recent reports from FlexOS and Robert Half are that remote work is a trend and the companies themselves are leaning on hybrid and fully remote models.

In conclusion, if you want to be an effective remote UX designer, then you need to stay in the loop on the latest tools and technologies, keep having a flawless communication with team mates and never stop honing your UX skills with the professional development. Embracing these practices will allow UX designers to thrive in the ever changing landscape of remote work.

The post How to Work Remotely as UX Designer in 2024? appeared first on Designveloper.

Today, computer vision and its applications are not something new to us. It appears everywhere in our daily lives, from the iPhone’s TrueDepth camera and Amazon Go’s Just Walk Out system to autonomous robotics in manufacturing plants. To help you better understand this fantastic technology, our article will discover its five common applications. From classifying images to tracking objects in real-time, it’s opening exciting opportunities to change our world.

But before breaking down these applications, we want to give you a comprehensive overview of how computer vision has developed recently.

Overview of Computer Vision

Briefly speaking, computer vision is a technology that allows computers to see and interpret people or objects in visual stimuli (e.g., images or videos). It works by using specialized software to analyze visual data collected from hardware like cameras and sensors. The technology also uses different techniques like image processing or statistical pattern classification to implement this process. 

History & Growth of Computer Vision

Computer vision first appeared in the early 1970s as the visual perception component that was expected to imitate human vision and equip robots with intelligent behavior. 

It differs from digital image processing which only manipulates and improves images through techniques like filtering or noise reduction. Computer vision, by contrast, aims at retrieving meaningful information from images, just like the human visual system can do. Particularly, its goal is to interpret the spatial arrangement of objects (“3D structure”) in a scene and understand the overall context of an image. Accordingly, it was expected to perform high-level tasks, like object detection or motion analysis. 

The following period of the 1970s-1990s witnessed the evolution of computer vision with advancements in image analysis techniques and hardware (like graphics chips and many-core architectures). Studies during this period also introduced various foundational algorithms, such as line labeling, articulated body models, image pyramids, edge and contour detection, or image segmentation. 

In the 2000s, the deepening interaction of computer graphics and computer vision transformed this realm significantly, with the introduction of recent CV algorithms like image-based rendering or feature-based recognition. Especially, the growing adoption of deep learning algorithms, typically Convolutional Neural Networks, has truly made CV outcomes more accurate. 

Besides technological advancements, the higher demand for safety and productivity has recently encouraged computer vision to develop. Particularly when COVID-19 suddenly exploded in late 2019, various organizations were finding ways to control and prevent infection effectively. Computer vision, therefore, became a crucial tool with common applications like masked facial recognition, thermography, or bacterial screening. 

Future of Computer Vision

Even when the pandemic ended, the global demand for this technology continued to soar. Researchers predicted this demand will grow by 27.3% annually from 2024 to 2032 with the following noticeable trends:

By Technology

• The increasing adoption of 3D imaging and automation technologies will boost the growth of AI vision which involves using artificial intelligence to understand visual data.
• Generative AI will be integrated to make computer vision systems more robust and generalized. It uses techniques like generative adversarial networks to create realistic images, enhance image synthesis, assist data augmentation, etc. 

By Industry

• The agriculture industry will see the growing use of AI vision in many tasks, like disease detection, plant monitoring, and yield prediction. Particularly, AI algorithms can analyze crop images, predicting the crop’s health and yield potential.
• Manufacturing still dominates the computer vision market due to its huge applications in boosting efficiency, minimizing waste, and avoiding potential failures. The technology can inspect products, spot their defects (e.g., minor cracks), and detect early signs of machinery deterioration. 
• Healthcare will witness the highest growth in using computer vision. The technology can analyze X-rays, MRIs, and CT scans to recognize fine abnormalities that can be invisible to the human eye, hence enhancing diagnoses.

5 Key Applications of Computer Vision

Computer vision has wide applications across industries, bringing them a variety of transformative benefits. In this section, we’ll dig into five common applications by computer vision’s typical techniques:

1. Image Classification

Image classification is a basic, yet important computer vision application. Its main goal is to train machines how to classify images based on their content – be it a cat, a bike, or even more complex objects. This categorization task focuses on identifying shapes, textures, patterns, and colors in images to sort them into the right groups.  

Computer vision systems leverage many techniques and algorithms for effective image classification. They involve feature extraction, Support Vector Machines (SVMs), Naive Bayes, Hidden Markov Models (HMMs), etc. 

Today, these systems also integrate deep learning methods to categorize images with higher accuracy. One of the most common techniques is Convolutional Neural Networks (CNNs). CNNs layer numerous filters over images to extract and classify different features (e.g., shapes or edges). 

Real-World Applications

Image classification has countless applications across industries. Below are some key areas where computer vision is utilized for this task:

• Medical Image Analysis: In healthcare, computer vision systems can analyze thousands of medical images (like CT scans or X-rays) to detect early signs or abnormal growths of disease. This helps doctors make faster, yet still precise diagnoses. 

• Product Classification in eCommerce: Online retailers such as Amazon or Walmart can use CV systems to automatically organize thousands of products into groups like “office furniture,” “home decor,” or “customer electronics” based on their images alone. This helps them manage large inventories with ease. 

• Land Use Classification: Governments (like Queensland) and environmental organizations are using computer vision to analyze satellite imagery and automatically classify land use features (e.g., forests, water bodies, or urban areas). This helps them track land use changes and manage natural resources more efficiently. 

• Wildlife Monitoring: CV systems can categorize images of animals captured by cameras in wildlife areas, which is specifically useful in wildlife conservation. Accordingly, researchers can collect data on species distribution, interpret migration patterns, and track endangered animals. 

2. Facial Recognition

Facial recognition is the sophisticated, yet most common application of computer vision. It uses both traditional and deep learning methods – for example, Principal Component Analysis (PCA), CNNs, and DeepFace – to identify specific facial characteristics. These features, like the distance between eyes or the jawline’s contour, form a “faceprint” to tell individuals apart. 

Computer vision implements the facial recognition process through two key steps: face detection and face identification. First, a CV system detects and isolates a face in an image or a video frame. Then, the system will compare the detected face against a database of known faces to identify whether the face matches a particular individual. These capabilities make computer vision a valuable tool for surveillance and security, especially in tracing criminals or missing individuals. 

Real-World Applications

Here are several impactful applications of vision-based facial recognition: 

• Access Control Systems: Many office buildings, government agencies, airports, and other facilities use computer vision to confirm people’s identities and block unauthorized access in access control systems. For instance, Delta Air Lines uses a vision-based kiosk at La Guardia Airport to take photos of travelers and compare them with the government database to identify their identities. This speeds up check-in and boarding processes while maintaining high security. 

• Law Enforcement: Vision systems can scan crowds in images or videos sent from security cameras and match faces against a government database. This helps police and security agents detect suspects, locate missing individuals, and secure public areas. 

• Social Media Platforms: Such social networking sites as Facebook rely on advanced CV algorithms like DeepFace for face verification and photo tag suggestions. By scanning uploaded images, these techs can identify and match familiar faces in previously posted photos. This allows you to automatically tag friends and organize your photo libraries.

• FaceID on Smartphones: Many smartphones now integrate facial recognition technology to help you unlock devices securely. Take Apple’s iPhones as an example. These products use a TrueDepth camera system to scan your face and compare it to secure encrypted facial data stored on the devices. This technology also enables you to log in to apps securely or verify your identity for payments.

3. Object Detection and Tracking

In addition to humans, computer vision proves useful in detecting and tracking objects in visual data. Object detection focuses on identifying and locating each object in a single frame. Meanwhile, object tracking traces these identified objects across different frames in a video. This allows the vision system to inspect their movement over time.

Vision systems can leverage traditional methods like Sliding Window, Haar Cascades, or Template Matching to identify and track simple objects with basic movements. For more sophisticated objects, they often use deep learning algorithms like YOLO, Faster R-CNN, or SSD. 

Particularly, YOLO (You Only Look Once) scans the whole visual data to detect the location of each object and what it is (e.g., a cat or dog) in one go, rather than breaking down the process into many steps. Faster R-CNNs (Region-based Convolutional Neural Networks) can directly identify potential areas (“region proposals) where an object could be instead of scanning every pixel. Meanwhile, SSD (Single Shot MultiBox Detector) uses various layers to draw estimated boxes around objects of all sizes to identify their location. 

Real-World Applications

Various industries have increasingly adopted object detection systems to enhance automation and streamline workflows. Below are several significant real-world applications of computer vision in this task:

• Self-Driving Vehicles: Many vehicles like Tesla’s Model Y use cameras and sensors to scan their surroundings, identifying objects (e.g., pedestrians, obstacles, or other vehicles) and tracking their movement. This allows them to navigate the roads, make smart decisions (e.g., slowing down), and ensure passenger safety.

• Traffic Monitoring Systems: Many places like New York, Singapore, and Barcelona use vision-based systems to monitor and analyze traffic flow. These systems use cameras installed on roads to identify and track vehicles, traffic lights, and potential obstacles (e.g., stalled vehicles). This reduces traffic congestion and improves road safety. 

• Robotics: Through cameras embedded, robots can understand and interact with their surroundings. In manufacturing plants like Ford or Peterson Manufacturing, for instance, vision-based robots can detect and load parts to an assembly line. Meanwhile, retailers like Walmart also use shelf-scanning robots to inspect aisles, monitor products and prices, and check for problems. Computer vision also plays a key role in robotic surgery (like in Mayo Clinic) to foster the precision of procedures.

• Retail Analytics: Computer vision has wide applications in retail analytics. By identifying and following shopper movements, stores can gain insights into foot traffic patterns, shopping behavior, and popular products. Many retailers like Amazon Go integrate this technology to scan what customers pick up and automatically tally the bills, which is often known as “self-checkout systems.” This technology also detects and tracks in-store and outside objects (e.g., fire extinguishers, automatic doors, or vehicles parking in front of stores) to ensure compliance with internal policies, smooth operations, and no obstacles blocking exits.

4. Image Restoration 

Computer vision makes profound impacts on image restoration. This application focuses on enhancing or restructuring low-quality images like old photos, noisy medical scans, or blurry surveillance footage. Its goal is to restore the original, clean version of the images to make it clearer or more helpful for analytics. 

For effective image restoration, computer vision first captures and analyzes the local structure of the visual data. This involves looking at even the smallest regions of the image to determine features like edges, lines, or textures. The step helps a vision system interpret the image’s underlying characteristics and patterns. 

Then, the system will use specialized algorithms and the analyzed information to process different types of damage. For example, deconvolution algorithms help reverse blurring effects, while such denoising algorithms as Wavelet Transform or Non-Local Means can eliminate unexpected noise. Deep learning algorithms, like CNNs and Generative Adversarial Networks (GANs), can recover degraded images with impressive accuracy. 

Real-World Applications

Image restoration has some noticeable use cases as follows:

• Medical Imaging: If medical images (e.g., X-rays or MRI scans) suffer from noise or blur, doctors hardly analyze images for accurate diagnosis. By enhancing image clarity, vision-based restoration can identify subtle patterns (like small tumors) that might be unnoticed.

• Forensics & Law Enforcement: Vision-based image restoration techniques are extremely useful for forensic investigations and law enforcement. By recovering old photographs and low-quality images from CCTV surveillance footage or crime scenes, police can easily identify suspicious individuals or objects that can be important for an investigation.

• Cultural Heritage Preservation: Various historical photos and documents suffer from damages or degradation issues over time (e.g., discoloration or fading). With advanced CV techniques, historians can bring out faded details and recover original colors.  

• Satellite and Aerial Imagery: Images collected from satellites or aircraft are sometimes distorted because of camera limitations, movement, or atmospheric conditions. By removing noise and improving sharpness, vision systems can address these issues, restoring images with clearly presented geographic and environmental features for later analysis.

5. Feature Matching

Feature matching is a crucial computer vision technique that detects identical features or parts between two or more images. It works by recognizing unique points in an image (“feature points”). These points, such as a building’s corners or textures, stand out from the rest of the scene. They have unique “fingerprints,” known as descriptors, to help computers identify and see whether there’s a feature match across multiple images. 

Computer vision uses specialized algorithms to ensure reliable feature matches. Two of them include SURF (Speeded Up Robust Features) and SIFT (Scale-Invariant Feature Transform). The former captures unique features for simple scenes, while the latter can handle more challenging matching cases regardless of image scale. 

Real-World Applications

With the mentioned capability, feature matching plays an important role in scenarios where you need to align, combine, and track images in real-time. Below are some of its real-world applications: 

• Image Stitching: Feature matching is widely adopted in image stitching, where various images are combined to form a larger panorama. Computer vision uses algorithms like image registration, calibration, and blending to identify overlapping regions and match the feature points. Image stitching is quite popular in tasks like document mosaicing, image stabilization, medical imaging, video stitching, and object insertion. 

• 3D Reconstruction: Feature matching also proves helpful in creating a 3D representation of a scene or an object from different 2D images. By recognizing and matching features from multiple angles, computer vision systems can calculate the structure and depth of objects to build a realistic 3D model. This capability turns it into a valuable tool in sectors like architecture or archeology. 

• Augmented Reality (AR): Using your phone’s camera to capture pictures of your environment, AR applications like the IKEA Place App understand the scene, detect feature points in the real world (e.g., tables or floors), and anchor virtual objects to those features. This helps the apps place the virtual items accurately in your real-world space. 

• Document Scanning: Phone cameras and several applications (like Google Translate) allow you to convert images or scanned documents into editable text. This process is often known as Optical Character Recognition (OCR). It uses feature matching to identify unique feature points and align these documents for precise text recognition. 

Conclusion

Now, you’re here, after a long journey of discovering common computer vision applications and its long-term growth. With impressive capabilities, computer vision has a wide application, from image classification and restoration to facial and object detection. In the future, advancements in modern technologies like GenAI will boost the growth of computer vision, giving it the ability to perform more complex tasks.

Are you looking for ways to apply this modern technology to your business? If yes, consider Designveloper as your reliable partner! We have extensive expertise and experience in incorporating computer vision into your operations and developing scalable AI solutions that meet your needs. Besides, we offer full-life cycle support, from planning to full deployment and ongoing maintenance, within your budget.

So why wait? Partnering with Designveloper today to revolutionize your business. Contact us and discuss your idea further!

The post Top 5 Computer Vision Applications Transforming Our Lives appeared first on Designveloper.

In recent years, the world has increased its dependence on software for most of its activities. However, to fulfill the demands of individuals or organizations, software needs to provide the required qualities, and functions and even be developed at an affordable cost.

Normally, those characteristics are more obviously affected by software architecture. It plays an important role in building the desired software. Without it, the whole process of writing software can be slowed, or even ruined. Keep reading and find out more about it!

Understanding Software Architecture

In this first section, we endeavor to help you understand the basics of software architecture.

What is Software Architecture?

People in the software industry have different definitions of architecture. Yet some of which do not suffice to define it completely and exactly. According to Roy Fielding, the creator of the REST architectural style and also co-author of the HTTP spec, software architecture is:

“… an abstraction of the run-time elements of a software system during some phase of its operation.”

Also, the architecture in the software itself is not only a fundamental structure to describe how systems work, but also more than that. As fully defined by IEEE 1471-2000, software architecture is “the fundamental organization of a system, embodied in its components, their relationships to each other and the environment, and the principles governing its design and evolution.” This definition reveals what software architecture truly includes. 

Architecting a system is the first step of any software’s lifecycle. It lays a solid foundation for software systems to be built on, by converting a series of attributes (e.g. performance, manageability, and security) to a successful application that meets technical or business expectations.

Software Architecture’s Role in Structuring Software Systems

Software architecture plays a pivotal role in shaping software systems. It defines how a system is structured, determining its behavior and the relationships between its components. This vital aspect of software development offers several key benefits.

First and foremost, software architecture provides the blueprint for a system. It defines the essential structures needed to understand and reason about the software. This clarity aids in creating and maintaining the software effectively.

Moreover, software architecture goes beyond just structure; it also delves into how the system behaves. It outlines the behavior of the system, encompassing software elements, their relations, and the properties of these elements and relations. This comprehensive view ensures that the software functions as intended.

Communication structure is another crucial aspect addressed by software architecture. It explains how components within the system interact and work together to achieve specific tasks. This understanding is fundamental for seamless system operation.

One of the key strengths of software architecture is its ability to balance stakeholder needs. It allows stakeholders to grasp how the system will meet critical qualities like modifiability, availability, and security. This transparency fosters collaboration and informed decision-making.

Furthermore, software architecture has a significant impact on team structure. It serves as a guide for project management, enabling them to allocate tasks efficiently to the teams and individuals involved. This alignment streamlines development efforts.

Lastly, a well-crafted software architecture focuses on significant elements, ensuring that the system can adapt and expand to meet future needs. This flexibility is essential in a rapidly evolving technological landscape.

The 4 Benefits of Software Architecture

To many stakeholders, software architecture seems tricky for them to perceive. Yet if no or poor architecture is built, many resulting problems will be caused, because:

1. It provides a solid foundation for a whole software project.

A poor architecture produces more Crufts which hinder developers from completely understanding systems and even stakeholders’ needs. So architecting software can help impose an overall vision for developers to better perceive the system, then know exactly how scalable the platform should be, and which quality attributes and functions users want in IT structure. Therefore, it can improve performance, enable risk management and cost mitigation, and avoid code deception. 

2. It gives a basis to reuse elements and decisions.

Many stakeholders often give the same requests for the desired software. Instead of building a completely new application, the reuse of elements and decisions can save design time and cost, and reduce the risk of failures and defects.

3. It helps communicate well with stakeholders to better meet their demands.

Sometimes, the expectations of stakeholders can go beyond the capability of software systems. The architecting ensures that software will be clearly understood and well discussed by all parties before reaching a consensus. Accordingly, it helps stakeholders to know what they get after the software is implemented. So, to avoid unexpected products, software architecture will be used. 

4. It makes code maintenance and improvement be better.

Completing software is not the final step of its lifecycle. There is more than that: maintenance and improvement. A good architecture enables developers to find bugs and anomalies more easily or promotes faster changes in IT systems. Thereby, it can fulfill the higher demands of users over time and avoid being out-up-date.

The 2 Characteristics of Software Architecture

To identify the properties of architecture, we need to answer two following questions:

1. What is Software Architecture made of?

Normally, software architecture includes such basic elements as components, connectors and data (Roy Fielding, 2000). Of which:

• Data are which contain information used and transformed.
• Components (or known as processing elements) perform those transformations of data through interfaces.
• Connectors (or known as connecting elements) allow communication between components by delivering data from one interface to another. 

Also, we should consider its configurations. Particularly, configurations are “the structure of architectural relationships among components, connectors, and data during a period of system run-time” (Roy Fielding 2000). However, a configuration can be thought of as a series of certain constraints for component relationships.

2. Which considerations are taken when architecting software?

Some factors affecting software architecture include:

• Stakeholders: The software is designed to serve stakeholders who have different requirements. Balancing those concerns is the top priority of software architecture.
• Separation of concerns: this concept shows the necessity to separate the concerns of all stakeholders by seeing architecture from different points of view.
• Quality attributes: different software will require a distinct set of properties (e.g. reliability, fault-tolerance, scalability, or security). Depending on demands, its quality attributes can vary.

• Architectural style: architects will use different architectural styles to address recurring problems.
• Conceptual integrity: this term is coined to show an overall vision of what software should do and how to do it. It helps all members understand the system and make it user-friendly.
• Cognitive constraints: are imposed to limit what software can do, and the lack of those constraints may ruin the architecture.

Common Software Architecture Patterns

Software solutions have become more complex owing to higher expectations of users. This complicates not only software development but also its maintenance and improvement activities afterward. Therefore, software architecture patterns appear to alleviate those problems. 

Particularly, a software architecture pattern is defined as a general, reusable solution to address existing and common problems and choose desirable qualities in software architecture. As described by Mark Richards, an experienced software architect, there are five ubiquitous patterns:

Layered (n-tier) architecture

It may be the most popular approach. Many of the largest software frameworks (e.g. Drupal, Java EE or Express) were developed on this pattern, so various applications built on them were also developed in the layered structure. 

It mostly includes four fundamental layers: presentation, business, persistence, and database. One of its benefits is the separation of concerns. Accordingly, requests will move from the top layer down to the bottom. For instance, data often originate from the presentation layer, after the layer is closed, such data will go through the business layer, then the persistence layer, and finally the database layer.

Event-driven architecture

This structure aims at managing all activities (e.g. production, detection, consumption, and reaction) related to events. It works by using a central unit to get all data and then assign them to different modules. For example, we can see a “car for sale” advertisement as a message presented by the retailer; after being transmitted on media channels, this ad can reach to potential customers. This advertisement can stimulate the “purchase” of those buyers. The change from “for sale” to “purchase” is seen as an event.

Microkernel architecture

This structure is often applied to execute product-based applications. It allows developers to download application packages, and add extra essential features that fit their requests. Those additional features can be seen as plug-ins to the core set of application operations, allowing extensibility and feature isolation.

Microservices architecture

Just imagine: You are the headmaster of a school. A decade ago, your school just had around some hundred students, which then has increased to hundreds of thousands. It was much easier to manage a small number of students and staff but is now more challenging to handle a larger one. Then you decide you divide your school into smaller single-function areas for better management and quality of education. This is also how Microservices architecture works.

It includes many small, independent services; each of which is self-contained and executes a separate business task.

Space-based architecture

After receiving requests from users, the database will process them. Yet if the load rapidly increases, the database server can hardly keep up with the load, and finally a whole website collapses. To avoid this problem, space-based architecture is applied. Accordingly, it includes two key components a processing unit and virtualized middleware. 

In short, despite the first stage of software’s lifecycle, software architecture significantly affects all activities, from deployment, and development to maintenance.

Conclusion

Understanding software architecture is crucial for any business aiming to build robust, scalable, and efficient systems. At Designveloper, we have already applied different architecture styles like microservices and cloud native architectures suited many different client cases. We know how to make sure your software is not only functional, but also future proof.

With cell based architectures a trend, and privacy engineering in high demand, 2024 is shaping to be an interesting time for software architecture. The importance of a well thought through architecture for lower latency, higher reliability, and reduced cost is brought out by these advances. When you’re partnering with Designveloper, you’re getting a hand from a set of reliable architects who have developed experience in these trends, and will be able to provide you with just the solutions you need.

Regardless of whether you are a startup or a large enterprise, we apply the same ground rules to our approach to software architecture, with the result that your project is based on a strong foundation. With a proven track record of delivering high quality software solutions, you can trust Designveloper to bring your vision to life.

The post What Is Software Architecture? Benefits, Characteristics and Examples appeared first on Designveloper.

The development time depends on multitude of factors such as features of the app, design complexity, the development team’s knowledge of required technologies, etc. With the progress in development tools and methodologies, the average time to develop a web app is slightly less, according to recent reports.

If you want deeper insight on the web app development process, Designveloper has a comprehensive guide for you. In this guide we break the stages of the app development process down and use some real world examples to give you a better idea of what factors into the timeline and how to make it go faster.

If businesses understand what influences success of a web app project, they can make better plans for web app projects to achieve success. Knowing the average timeline is important for project management and budgeting, whether you work with in house team or outsourcing to the development.

Why You Should Build A Web App

In 2024, it’s never been more relevant to create a web app. As digital landscapes continue to evolve, businesses and individuals have a real need to stay ahead.

Statistics of recent time corroborate the growing importance of web app development. By the end of 2024, the population of software developers in the global population is expected to reach of 28.7 million. Meanwhile, Node.js as it is the hottest web framework for developers, with 40.8% of developers using it. The global software development market is forecasted to reach $1039 billion by 2027, growing at a compound annual growth rate (CAGR) of 22.54% during the forecast period (2020 – 2027).

Moreover, about 54% of software engineers find themselves more productive when they work from home. Software development projects typically cost $3,000–150,000, but can be more than $1 million for complex ones. At the same time this represents a dynamic industry that is rich with opportunity for businesses.

What is a web app?

A web app, or web application, is a computer program running on a web server. Contrary to the traditional desktop applications, we use web browser to access web apps. They are a mix of applications and sites featuring interactive user experience.

There are many web apps used in different industries such as eCommerce, media, healthcare and education. High accessibility, amount of accessibility, cost effectiveness, and easy updates are the obvious benefits they have provided.

Recommended reading: Web Application Examples and Definition for Beginners

Examples of notable web apps

Interactive experiences on web apps are becoming an integrated part of our daily lives on any device. Here are some notable examples:

• Google Docs: Users can create, edit and share documents online, easily.
• Spotify: Offers personalized music streaming.
• Airbnb: Connects travelers to unique accommodations around the world.
• Facebook: Allows users to connect and communicate with friends and family, sharing.
• Amazon: Their vast product range offers a seamless shopping experience.
• Twitter: This platform allows users to share short message and keep updated with real time information.
• Pinterest: Helps users find and save ideas from different sources online and across the entire web.
• Tinder: Connects people in need of romantic relationships.
• Uber: Offers convenient means of transportation.
• LinkedIn: Assists users to connect with colleagues and seek jobs.

This demonstrates how web apps can occupy any segment of the industry. It shows how web apps improve user experience and makes several actions easier.

Main benefits of a web app

Building a web app in 2024 presents numerous opportunities. It’s It’s no longer enough to have an online presence; it’s about tapping into a vast array of advantages that can propel your business or project to the next level. So, here in this section, let’s see why a web app is built. The benefits of web app development include everything from cost effectiveness to greater user engagement, so knowing that can help to inform your decision to embark on your web app journey.

Accessibility and cross-platform compatibility

Web apps are delivered over the Internet, are used by entering a web address in a web browser and can be accessed from any device that has a web browser for example PC, Mac, tablets and smartphones. That would mean your app could be used by anyone on the wider web – without having to download anything.

Cost-effective development

It’s usually cheaper to develop a web app than to make apps for native platforms. You save on development and maintenance costs because you have only one codebase.

Ease of maintenance

Web apps are maintained on the server, therefore all updates are centralized and easier to deal with. This lessens the need of multiple update at a time from several devices.

Scalability and third-party integrations

Web apps are easy to scale as user base grows and integrate with other Services and APIs to improve functionality and user experience.

No download required

A web app doesn’t require users to download or install anything. Going this route can drive higher user engagement, and ultimately retention.

With web apps, you get a more interactive and engaging user experience, which means you have a greater chance of increasing customer satisfaction and loyalty.

Improved customer engagement

Web apps provide a more interactive and engaging user experience, which can lead to increased customer satisfaction and loyalty.

Enhanced efficiency and productivity

For businesses, web apps streamline processes for better efficiency and productivity. This is time and resource saving in the long run.

Increased competitive advantage

A web app can provide you an edge over other businesses having the same services by letting you add a feature or use cases which might not be enough to offer or implement by other competitors.

Today web apps represent a wise investment, where you can potentially earn much back through their accessibility, cost efficiency, and user satisfaction. Are you planning to develop a web app? Then the time is just right.

How Long Does It Take to Build A Web App?

A typical web app built to meet the needs of a business usually takes a lot of time to develop because it has so many features, management tools, and access levels. But moving quickly through the process isn’t the best way to do it. If you don’t do it carefully, it could hurt the overall quality of the solution.

It usually takes 4.5 months to build a front-end web app and a back-end infrastructure from start to finish. If the project is big, it may take a few more months. On the other hand, if the team already has some modules, the project could be finished and adapted to each person’s needs in 3.5 months.

According to Altamira, the durations for specific functionalities are as follows:

Recommended reading: Choosing Web App Development Services: 5 Essential Tips

Estimation difficulties

It’s hard to gauge how long it takes to build a web app. It also depends on a lot of factors: complexity (or lack thereof) of the project, experience level of the team, and so on. The average development time is between 18 weeks according to recent reports, but this can vary widely. How long it’ll be will depend on the type of app you want to make, but a simple one can take up to a few months, while a more complex one can be over a year.

Before we can be a little clearer, some examples will help. According to a study by Designveloper, front end web apps usually take 4.5 months to be completed; however, back end infrastructure could take just a little bit more. According to another report, some modules might be done even in as little as 3.5 months, if the team has already had some of them.

These are the variables you need to understand to set and manage expectations in the client’s timeline. This helps developers to plan and develop well what they are going to do.

Methods for reducing web app development time

In 2024, building a web app can be a time-consuming process. Designveloper, as a leading software development company, has successfully implemented strategies to reduce development time on projects like the SaaS platform for Joyn’it and the healthcare platform for ODC. Here are three proven methods to save time:

Leverage pre-built components and frameworks

Pre built components and frameworks can save us a lot of development time. There are frameworks such as React.js, Vue.js or Angular that supply you with ready builds or libraries that make work easier. Statista reported these frameworks are the top choices for developers in 2024.

For instance React.js is component based architecture that simplifies building user interfaces. This method helps developers reutilize certain components which are less time and effort consuming. Similarly, Vue.js provides a flexible and easy to learn framework and reduces the time taken to develop.

Using these frameworks lets the developers not reinvent the wheel and drive their web app towards a more unique feature. By using this method, the development process is sped up, as well as the final product is consistent and reliable.

Adopt Agile methodologies

The flexibility, the collaboration and the continuous improvement from using Agile methodologies have revolutionized the development of web apps. A report from Intelivita says Agile can shorten development time by up to 30%. The key point is that by splitting a project into smaller chunks and having dozens or hundreds of volunteers testing and providing feedback, it means that a project can be finished quickly.

Scrum and Kanban are popular Agile frameworks. Whereas Scrum is focused on short iteration called sprints, Kanban is about continuous delivery without overwhelming the team. Agile programs have brought down delivery times at companies like Cisco and Sony and improved customer satisfaction.

This is why Agile is so important in web app development; it allows developers to quickly change and build a high quality web app in a comparatively short amount of time. The primary benefit of this approach is manifested when requirements are required to change at any given time and time is short.

Utilize cloud services

Cloud services can save web app development time significantly. 60% of corporate data is already stored in cloud, according to latest statistics. Because of this shift in focus towards cloud platforms, Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) have become more common. These utilize alternate platforms that provide a scalable infrastructure and hence speed up the development processes.

For example, 48% of surveyed developers use AWS — It’s the most popular cloud platform among developers and it’s easy to see why. We can use cloud services so developers can concentrate on coding and not infrastructure. Additionally, this approach enables real time collaborations and auto testing speeding up the development cycle.

In addition, cloud services enable cost—effectiveness. Migrating to the public cloud can cut the Total Cost of Ownership (TCO) by up to 40%, according to a report by Accenture. Being not so expensive, plus with flexibility and scalability of the cloud service, cloud services are a preferable choice for the web app development.

To summarize, cloud services help save time during the development process and moreover are a cost effective and highly collaborative alternative for both internal and external collaborators. Therefore cloud adoption can be a strategic move for businesses that are looking to simplify their web app development process.

Build Your Web Apps With Designveloper

One of the most common questions that clients ask when they’re looking to develop a web app is, “How long does it take to build a web app?”. The answer to this question depends on various factors, including the complexity of the project, the number of features, the development methodology used, and the team’s size.

At Designveloper, the company follows an Agile development methodology that focuses on delivering working software in short iterations, allowing us to deliver high-quality software in a shorter amount of time. They have a dedicated team of developers, designers, and project managers who work together to ensure that each project is delivered on time and within budget.

Our web app development timeline

The timeline for developing a web app can vary widely, depending on the project’s scope and complexity. Simple web apps with basic features can take anywhere from 4-6 weeks to develop, while more complex web apps with advanced features can take anywhere from 6-12 months or longer.

When you work with Designveloper, they’ll provide you with a detailed project plan that outlines the timeline for each phase of the project, including design, development, testing, and deployment. They’ll work closely with you to ensure meeting your business needs and that the project is delivered on time and within budget.

Conclusion

It’s not always easy to guess how long it will take to build a web app, but you should hopefully have a better idea after reading this post. You could always choose a web development company with a lot of experience to assist you through all steps. At Designveloper, we put a lot of emphasis on careful planning and keeping open lines of communication with our clients. We will do everything we can to explain each step of the process and make sure it meets your needs. All you have to do is get in touch with us, tell us what you need, and we will take care of the rest.

The post How Long Does It Take To Build A Web App in 2024? appeared first on Designveloper.

Because how people get information and communicate has changed, if businesses want to stay relevant, they must have an online presence. And more generally speaking, they must transform themselves into an e-commerce business.

What is an eCommerce Business?

People often think of eCommerce as websites for buying and selling products like Amazon. However, a broader definition of eCommerce involves much more than that. The UK government, for example, defines eCommerce as below:

“E-commerce is the exchange of information across electronic networks, at any stage in the supply chain, whether within an organization, between businesses, between businesses and consumers, or between the public and private sector, whether paid or unpaid” (Cabinet Office, 1999)

By this definition, we can see that eCommerce business is not only about financial transactions but also about non-financial transactions, together with pre-sale and post-sale activities. Kalakota and Whinston (1997) attempted to list different perspectives on eCommerce:

1. A communications perspective: the delivery of information, products or services, or payment by electronic means. I.e., Forbes, albeit a website for news, is actually an eCommerce company. 
2. A business process perspective: the application of technology towards the automation of business transactions and workflows. I.e., The emergence of food delivery services like Uber Eats provides a solution to the transportation problem of many restaurants. 
3. A service perspective: Enabling cost-cutting at the same time as increasing the speed and quality of service delivery. I.e., with emails, we no longer rely too much on postal services. 
4. An online perspective: the buying and selling of products and information online. This is too obvious in the case of Amazon or eBay.

Recommended reading: The Future of Shopping is Here: AI-Powered eCommerce Mobile Apps

Buy-side and Sell-side eCommerce

Moreover, eCommerce transactions are not only between an organization and its customers but also within an organization, and between an organization and its stakeholders, not limited to customers.

In fact, when people use the term eCommerce, they usually refer to the specific selling and buying activities between a company and its customers. This, however, is just one part of the whole picture. When you run an eCommerce business for sales, you can be both a seller and a buyer. You buy products and services from some suppliers; and at the same time, you sell your own products and services to some consumers. This is why when people evaluate the strategic impact of eCommerce on an organization, they often distinguish between buy-side eCommerce, the transactions to procure resources needed from suppliers, and sell-side eCommerce, the transactions to sell products to customers. You can take a look at the following figure to have a clearer picture:

Different Types of Buy-side eCommerce

The buy side of eCommerce refers to the business to business sales, where organizations purchase needed resources from the suppliers. This kind of eCommerce supports the upstream supply chain, i.e. from procurement to inbound logistics. Here are some key types:

• The transactions between businesses are called Business to Business (B2B). For instance, a supplier that sells raw materials to a manufacturer. Shopify reported that in most cases B2B is about high volume orders and a tailored solution.
• Business to government (B2G) transactions are the transactions between businesses and the government entities. For example, a tech company supplying a government agency with software solutions. Public sector procurement has a critical dependency on this model.
• Consumer-to-Business (C2B) involns whereves transactio consumers sell products or sell services to businesses. As an example, a freelance graphic designer who buys services to sell to a company. With the rise of gig economy platforms, this model is becoming increasingly popular.
• Consumer to Government (C2G) refers to transactions in which government is the buyer, and consumers are the sellers, supplying services or products. For example a citizen who submitts a bid on a public project.

Buy side eCommerce helps companies optimize their supply chain by reducing costs and improving efficiency. The commerce is an essential shift for businesses to do more quickly, and properly.

Different Types of Sell-side eCommerce

Sell-side eCommerce often involves using Internet technologies to market products or services. The products are not necessarily physical ones like books or clothes. Spotify, for example, does not sell concrete music CDs but music streaming services.

Also, in many cases, the websites are not for the sake of financial transactions but for branding and other marketing activities. It is thus possible to classify the online presence of sell-side eCommerce, or eCommerce websites, into 4 main types:

• Transactional eCommerce sites: The main contribution of these sites is through online purchases of products. They can be retail sites (Amazon), travel sites (Air BnB), and online banking services (www.hsbc.com).
• Services-oriented relationship-building websites: These sites mainly serve as the place where people come to get information about the business. They stimulate offline sales and general inquiries or leads from potential customers. 
• Brand-building sites: Products are not typically available for online purchase on these sites. They support branding, and they are typically suitable for low-value, high-volume fast-moving consumer goods (FMCG brands). Some examples of this type are Tango (www.tango.com), (www.guinness.com).
• Portal, publisher, or media sites: NYTimes, Forbes, The Guardian, and similar websites for news and entertainment are also regarded as eCommerce sites. These sites generate revenue through advertising, commission-based sales, or the sale of customer data.

eCommerce vs. eBusiness

Many times eBusiness and eCommerce are used interchangeably, but they have different meanings. eCommerce is centered in online transactions of goods and services. Conversely, eBusiness involves all parts of running a business online, such as marketing, customer service and supply chain management.

According to recent statistics, the global e commerce sales destined to be $6.3 trillion in 2024. The growth in the use of these terms underscores the need to understand the distinctions between them.

Amazon and eBay are examples of eCommerce because transactions take place between customers and sellers. eBusiness examples are companies such as Salesforce, who implement end to end business operation solutions on an online platform.

Recommended reading: What is Cloud eCommerce Solutions?

Recommended reading: What is B2B Ecommerce? All You Need to Know about B2B Ecommerce

The Role of Digital Marketing in eCommerce Business

Since all business transactions are now electronically mediated, a new type of marketing also came into existence: digital marketing. It involves the management and execution of marketing using electronic media such as the web, e-mail, and wireless media in conjunction with digital data about customers’ characteristics and behavior. 

To put it simply, digital marketing shifts the focus of communications away from traditional means such as newspapers, radio, and television into blogs, podcasts, social networks, SMS, and such-like. But still, all the traditional marketing channels are not necessarily abandoned. Both offline and online channels are important to gaining new customers and maintaining relationships with existing customers. A successful eCommerce business would know how its target customers communicate and put the emphasis on the right channels. That’s the basic principle of marketing.

Benefits of Digital Marketing for an eCommerce Business

Digital marketing offers numerous advantages for eCommerce businesses, helping them reach a wider audience and boost sales. Here are some key benefits:

Global Reach

Digital marketing allows eCommerce businesses to reach customers worldwide. Online marketing is not limited by geography unlike most traditional marketing. It creates new markets or new growth opportunities.

Cost-Effective

Digital marketing is more affordable than traditional marketing methods. Targeted strategies don’t need a huge budget, and can allow small businesses to compete with larger companies. For instance, even no investment is required to start SEO and social media marketing.

Targeted Audience Engagement

Through digital marketing, businesses can target a specific demographic. Data analytics are used by businesses to craft personalized marketing campaigns that are direct to the point. Consequently, conversion rates are higher and the general satisfaction with customers is higher.

Measurable Results

Digital tracking gives you options that traditional marketing lacks, such as measureable tracking of results. Google Analytics is a great tool for businesses to monitor website traffic, conversion rates etc. The data is used in making informed decisions at the level of the business and optimizing marketing strategies.

Improved Customer Connections

Better customer relationships are brought about by digital marketing. Businesses are able to directly engage and gain loyalty from customers through social media and email marketing or other relevant online channels. It results in repeat business and word of mouth referrals.

24/7 Availability

Unlike physical stores, eCommerce businesses can operate around the clock. With digital marketing, products and services are always available for people to purchase, even when the time isn’t right for you to put down your camera.

Enhanced Brand Visibility

With digital marketing, increasing brand visibility and awareness is achieved. SEO, content marketing, and social media are used to improve businesses presence online along with bringing in new visitors.

Competitive Advantage

Digital marketing is a competitive edge for businesses in a crowded online marketplace. Staying on top of marketing trends and using the newest tools and techniques keeps a business in a different class from the competition.

Recommended reading: B2C Ecommerce Model: Definition, Case Study and Compare With Other Models

Drivers & Risks of an eCommerce Businesses

The Internet provides significant opportunities for many businesses to build closer relationships with their existing customers and suppliers to help achieve customer retention. In particular, there are a variety of benefits that drive the adoption of eCommerce business models.

1. Competitiveness drivers:

With new communication channels, businesses can reach a larger customer base. They can also encourage loyalty and repeat purchases among existing customers in order not to lose market shares to businesses that already use eCommerce.

2. Cost/Efficiency drivers:

Delivering services electronically helps reduce staff costs, transport costs, operating costs, and costs of printing materials. The speed with which supplies can be obtained and goods can be dispatched will be increased.

But opportunities have to be balanced against the risks of introducing e-business services which vary from strategic risks to practical risks. 

Recommended reading: Ecommerce Website Image: 10 Tips to Optimize

3. Strategic risks:

Making the wrong decision about e-business investments, for example, is one of the main strategic risks. You may have lavished your capital on e-business but did not achieve the hoped-for returns, either because the execution of the plan was flawed, or because the planned approaches used for your market were inappropriate. 

It is important to know that the impact of the Internet and technology varies by industry. Sometimes, it works like a typhoon force, a ten times force. Sometimes, it is just a bit of wind. Asking yourself whether your business needs Internet adoption is a must before making any decision on e-business investment. 

4. Practical risks:

Apart from strategic risks, there are also a couple of practical risks you should know: 

• Web sites may fail if they cannot handle a spike in visitor traffic.
• Hackers may penetrate the system’s security and steal credit card details.
• Cold emails may disturb some customers if sent out without their permission. This might sometimes break the privacy and data protection laws.
• Customer orders might go missing or be delayed, and disappointed customers will never return.

There are also certain barriers to the development of online technologies, such as the costs for set-up and maintenance, the lack of time/resources, the lack of skills and knowledge (staff), difficulties in integrating IT systems, or difficulties in changing processes. These might as well hinder your business from getting the most out of ICT adoption.

Recommended reading: Top 18 Web Development Companies in Vietnam

The eCommerce Environment

With the rise of eCommerce businesses, not only business models but also the structures of the industry and the marketplace have changed. For example, previously, B2B companies sold their products through a network of distributors. But now with the advent of e-commerce, they can bypass distributors and trade directly with customers via a website. And a new “force” arises and plays certain roles in marketing, which is online intermediaries, specifically search engines, review sites, price comparison sites, social networks, blogs, and other publisher sites.

So to evaluate all the opportunities and threats that an eCommerce business is facing and accordingly make an appropriate strategy, it is important to continually monitor the environment in which the business operates, which includes micro-environment and macro-environment:

1. Strategic agility

In this regard, there is at least 1 concept that every business owner must know: strategic agility. It is the capability to innovate and so gain a competitive advantage within a marketplace by monitoring changes within an organization’s marketplace, evaluating alternative strategies, and then selecting, reviewing, and implementing appropriate candidate strategies. To put it simply, this concept is somewhat similar to Eric Ries’ “lean startup” and the philosophy of Agile project management methodology.

It prioritizes adapting to changes, rather than sticking to an initially projected action plan

It is important to find anomalies in the marketplace where it doesn’t appear as expected and these may represent learnings or opportunities. Detailed customer insights and business performance are necessary to identify these anomalies. By paying close attention to all the changes of the micro and macro environment and adjusting the business plans accordingly, business owners can act rapidly and bring about the best outcomes possible.

Dell Computer, for example, has spent relatively little on research and development but has instead been constantly probing the marketplace, trialing new eCommerce business ideas with multiple probes into the approach. They are an exemplar of a company with strategic agility.

2. Online marketplace analysis

Whenever you want to develop a long-term business plan or create a short-term digital marketing campaign, it is necessary to analyze the marketplace. Right below is a sample map that helps you quickly grasp the linkages between online businesses and traffic flows.

There are four main elements in the above map:

Customer segments:

Knowing how your audiences consume online media, how they buy goods online, and the type of content they often search for from the intermediaries will help you target your marketing campaign in the right direction.

Search intermediaries:

Search engines like Google, Baidu (China), Yandex (Russia), or Naver (South Korea) are the intermediaries where audiences come to look for the content they want. These intermediaries, therefore, provide every eCommerce business with useful data to create personas for key audiences and analyze the current popularity of your website and competitors’ websites. Also, this is going to be a rich source of visitor traffic if you pay attention to SEM (search engine marketing).

Intermediaries and media sites:

These sites attract visitors via search or direct (if they are mainstream brands); thus, it is great if your eCommerce business can assess the potentiality of these sites.

Destination sites:

These eCommerce platforms also have another name, landing pages, where you want your customers to visit and carry out the expected actions (filling in a form, buying a product, and so on).

Conclusion

The ecommerce business landscape is rapidly evolving, with new models and technologies emerging constantly. As statistics go, global ecommerce revenue is expected to surpass to $8 trillion by 2027 proving the immense potential of this sector. This transformation is being led by companies like Designveloper; businesses like ours build upon massive experience in the web and software development to help businesses succeed in the online marketplace.

One evidence of Designveloper’s success is delivering state of the art solutions and projects using the latest tools and technology. Partner with Designveloper to overcome the myriad challenges of an ecommerce environment and leverage cutting edge trends and opportunities.

To find out how Designveloper can support your business to thrive, learn more about us on our website and see examples of our work.

The post ECommerce Business: Definition, Models of Transactions, and eCommerce Environment appeared first on Designveloper.

Computer vision (CV) is a powerful technology that connects cameras to advanced software to collect and analyze real-time visual data (like images or videos). In retail stores, the data can be about customer behavior, product arrangements on shelves, in-store staff activity, and more. Using this data, you can gain meaningful insights to make informed decisions for your store. 

If you want to learn more about CV applications in the retail industry, keep reading! In this article, we’ll explain why you should invest in this technology and on what aspects of retail it makes a real impact. Now, let’s take a look!

Should You Use Computer Vision for Your Retail Store?

There’s a fact that computer vision has received much criticism about its accuracy and ethical issues in recent years. Many people doubt that the introduction of this technology to retail stores would increase dependency, leading to significant layoffs and a loss of human ability to handle operational problem-solving. 

In some cases, CV can collect visual data from customers for personalized advertising or from in-store staff for employee monitoring. This can easily result in privacy violations or security risks if your store uses unapproved CV systems or implements weak data protection practices in place. 

This raises a big question: is investing in computer vision worth those problems? The answer is yes. Despite the existing drawbacks, computer vision still brings transformative benefits to your retail store if harnessed properly. Here’s how it can make a big difference:

Increase Efficiency & Minimize Costs

Computer vision technology makes your retail operations more effective. It supports automated inventory management by inspecting stock levels and reordering to ensure shelves are always full. 

Besides, CV systems help reduce shrinkage. In the retail industry, shrinkage means the loss of inventory that’s not sold for some reasons like misplaced items, theft, or incorrect pricing labels. CV systems can inspect on-shelf products in real-time through visual data analytics to limit this issue. This will decrease manual tasks, giving in-store staff more time to focus on customers and avoiding shrinkage-incurred costs. 

Additionally, computer vision can analyze customer traffic patterns and determine peak shopping times. This helps you schedule employees effectively to avoid overstaffing (too many employees) or understaffing (too few employees) in the store. As a result, you can save labor costs while ensuring service quality. 

Boost Customer Experience 

Computer vision enhances the shopping experience in many ways. First, your store can offer self-checkout systems and smart carts to automatically scan items for billing. This helps your customers avoid long queues.

Second, computer vision techniques can analyze customer movements through a retail heat map to point out which sections are most frequented. This enables you to optimize store layouts for better traffic and product arrangement. Third, for more advanced setups, CV systems can identify customer emotions, types of membership, and even past purchases to personalize in-store advertising and product suggestions. 

Assist Data-Driven Decisions

Computer vision collects real-time visual data from cameras. This data tells you about customer behavior, product popularity, and traffic patterns. So, you can make smarter decisions about inventory and marketing strategies. For example, if it shows which products are sold slowly, you can adjust store layouts to make them more visible or devise promotional programs to boost sales. 

Reinforce Security

Computer vision adds a layer of security to your retail store by spotting fraudulent activities (like shoplifting) and alerting staff in real-time. This reduces inventory loss and makes stores safer for both employees and customers.

10 Common Applications of Computer Vision in Retail

To help you better understand these benefits, we now explain how computer vision systems are adopted in today’s retail stores. Here are ten popular applications of this advanced technology you should consider: 

1. Inventory Management Automation

Computer vision is revolutionizing the way brick-and-mortar stores manage inventory. By using security cameras to constantly scan an entire store, it can automatically count inventory in real-time. If a CV system detects out-of-stock products or misplaced items on shelves, it’ll promptly alert store associates for restocking or reorganizing. This not only reduces manual checks but also keeps inventory always balanced.

Even when combined with predictive analytics, computer vision can forecast customer demands to optimize inventory levels. As such, you can understand what and when customers make purchases to stock items in the store better. 

Understanding the growing importance of computer vision, various retailers like Home Depot and Auchan have integrated it into their stores. For example, Auchan used Neurolabs’s “Reshelf” technology to inspect on-shelf availability in real-time and alert staff employees about out-of-stock products.

Other retailers like SpartanNash or Schnuck Markets even utilize autonomous inventory robots powered by computer vision. These robots can roam store aisles and scan shelves to check inventory levels. For instance, Schnuck has deployed its grocery chain robot called Tally to automatically collect on-shelf data like inventory position, price accuracy, and even promotional execution. Tally can identify out-of-stocks 14x more effectively than manual checks and reduce the times items are unavailable on shelves by 20-30%. 

2. Self-Checkout Systems & Smart Carts

Imagine this: your customers walk into the store, scan your store’s proprietary app, pick up items for automatic billing, and walk out. No more waiting in long lines in front of a cashier counter. Today, this isn’t a fictional idea. In 2018, Amazon introduced a “Just Walk Out” technology through its Amazon Go stores. This concept began the era of self-checkout systems and removed the traditional checkout process completely. 

The idea behind Just Walk Out is quite simple. Customers first scan their app at the gate entrance. Amazon Go then uses computer vision, combined with sensor fusion and deep learning, to track what customers pick up, add these products to their virtual carts, and automatically charge their account when they exit. 

Amazon continued to apply its self-checkout technology to replace physical carts. In some Amazon Fresh stores, smart carts, known as Amazon Dash Carts, are integrated with cameras and sensors to identify the price and automatically tally the bills of items that customers shop. 

This self-checkout concept has encouraged a cashier-less shopping trend across many other retailers like Walmart, Family Mart, and Kroger. Accordingly, the global demand for self-checkout systems is predicted to grow by 10.4% annually from 2024 to 2034. These systems speed up the checkout process and eliminate inconveniences (e.g., long queues and manual scanning) that can dissatisfy the shopping experience.

3. Queue Management

In addition to self-checkout systems, various retail stores still maintain traditional checkout methods. So, what have they done to manage long lines at the cashier counters and boost customer experience? 

Let’s look at the case study of Tesco – a British multinational retailer. The company uses the “Smartlane” system that includes thermal imaging cameras and infrared sensors installed on the ceiling to sense the number and behavior of customers at checkout. 

Plus, the system can automatically predict queue length and waiting time, helping managers to decide whether to open additional registers. This proactive approach allows Tesco to handle queuing issues quickly, optimize staff allocation, and accelerate service. Additionally, the adoption of computer vision helps keep wait times shorter, improve the shopping experience, and encourage shoppers to return. 

4. Customer Behavior Analysis

Computer vision, reinforced by deep learning algorithms, helps many retailers like Sephora, ATU Duty-Free, and Samsonite understand customer behavior in new ways. 

First, a vision system can count how many people visit a store per hour in real-time. Take Sephora as an example. This French brand used AllGoVision’s vision solution to analyze video streams from the Axis cameras installed at the entrance and near product sections. The system counts the number of visitors crossing a virtual line drawn in the camera view and sends real-time reports directly to the PoS systems. With the data, Sephora can understand customer traffic, peak times, conversion rates, and product performance. 

Second, computer vision can analyze foot traffic data collected from cameras or sensors to identify a shopper’s journey and high-traffic areas through a heat map or spaghetti diagram. It can also use techniques like image classification to recognize crucial customer behaviors within certain sections, like using trolleys or self-checkouts. 

Third, CV algorithms can estimate dwell time, or how long they stay in specific areas. If customers go straight ahead to a specific area upon entering and linger near certain items, the system can indicate high interest. Accordingly, you can arrange less popular, yet relevant products on the way to that section to encourage sales. 

Finally, CV can observe how customers engage with individual products, like picking up, examining, or placing them back. This gives you a better understanding of what appeals to customers (like packaging or free gifts). Also, machine vision can track how store associates interact with customers in real-time. This provides a better sense of in-store service quality. By analyzing these behaviors, you can modify product displays and improve customer service for a more engaging shopping experience.

5. Personalized Advertising

Computer vision can identify particular customers when they enter the store and provide personalized in-store adverts. 

How? Particularly, cameras identify a customer’s important details like age, gender, or facial expressions. Deep learning algorithms then can classify and analyze customers based on these details. 

Imagine a female customer standing near a camera in a skincare product section. Computer vision can estimate her age and evaluate whether she looks happy, dissatisfied, or neutral toward a particular product. 

Based on sentiment analytics, the screen can show ads that fit her profile and mood in real-time, like displaying ads for trendy products or new arrivals if it identifies a young lady. This approach makes ads more relevant and appealing to the customer. Plus, it provides the customer with a unique shopping experience in the store.

6. Loss Prevention and Theft Detection

Recognizing suspicious activities like shoplifting or sweethearting is one of the key applications of computer vision in retail. It uses deep learning algorithms to monitor human behaviors, detect patterns, and make informed decisions based on the input data. 

For example, when computer vision watches products being taken but not scanned at self-checkout counters, it’ll flag them as potential fraud and send real-time alerts to staff.  

Machine vision can identify unauthorized access to restricted areas (e.g., in staff-only areas or behind the cashier counter). Even when your shop is closed, computer vision systems can use techniques like automated people detection to discover intrusion events.

With these capabilities, computer vision is increasingly adopted in brick-and-mortar retail stores to prevent fraudulent activities. Walmart has implemented a machine vision technology, known as Missed Scan Detection, to recognize which products move past checkout registers yet are not scanned for billing. The system uses cameras to watch items passing through the registers and signal unusual activities to store associates. This technology has enabled Walmart to decrease rates of theft, fraud, and scanning errors.

7. Quality Control

Computer vision helps your retail stores control product quality efficiently. It can check product surfaces through high-resolution cameras to identify visible signs of damage, like cracks, broken packaging, or dents. 

This technology is especially useful in monitoring perishable products like fruits, vegetables, meats, or dairy. Reinforced by advanced algorithms, machine vision systems can analyze and detect shapes, colors, or textures that indicate signs of ripeness or spoilage. If products are visibly deteriorating or close to expiring, the systems may notify store employees to remove or discount to avoid waste. 

Kroger, one of the US’s biggest supermarket chains, uses computer vision and analytics to recognize early signs of quality deterioration. This approach enables the company to ensure the high quality of goods and avoid potential health risks incurred by damaged or spoiled items. 

8. Augmented Reality (AR) Mirrors

In 2012, Uniqlo made the whole retail industry “wow” with the world’s first virtual mirror in its San Francisco-based flagship store. It’s a traditional mirror with a digital display behind the glass. 

Powered by computer vision and augmented reality (AR) technologies, the magic mirror allowed customers to try on up to 120 coats within a minute. This eliminates the need to wear physical clothes and reduces long waits for fitting rooms, fostering a shopping experience and personalization. 

Uniqlo opened a new era of virtual mirrors across the retail industry. By using advanced computer vision techniques, AR mirrors can detect a shopper’s key details (e.g., body contours or facial features) in real-time to display the chosen item on the customer’s body or face in real-time. 

Also through AR mirrors, retailers can collect meaningful data about customer preferences. For instance, your store can follow which items are most frequently tried on and modify inventory to meet demand.

9. Employee and Compliance Monitoring

Computer vision technology can support human managers in managing store employees and ensuring compliance with standard operating procedures (SOPs). 

Particularly, vision systems analyze the images and videos of staff to identify whether they’re complying with internal policies, like greeting customers, wearing uniforms as required, or using face masks during the quarantine period. 

The systems, reinforced by machine learning algorithms, can inspect adherence to SOPs. These SOPs may involve store opening and closing times, branding policies, cleanliness of premises, customer management, and more. 

For instance, machine vision can detect whether your store is following the correct product placement, like displaying items of a particular brand at eye level. Or it can be used to identify if the shop’s floor, washrooms, and counters are cleaned after operating hours. When it discovers any policy violations, it’ll promptly notify store employees for fixing. With computer vision techniques, human operators have more time to focus on more critical and complex operating tasks.

10. In-Store & Outside Inspection

Smart security and surveillance cameras can be integrated with computer vision to continuously monitor in-store and outside events. 

Inside your store, smart cameras can capture and understand analog controls and temperature displays on appliances like thermostats or air conditioners. Combined with machine learning algorithms, the vision system can compare readings from these devices to preset thresholds and notify employees to take corrective action. 

It also automatically inspects whether fire extinguishers, sprinklers, and other safety equipment are continuously available. With vision-based cameras, your store is always kept safe from unexpected disasters like fires caused by AC overheating. 

Further, the system can recognize obstacles stopping in-store customer flow (e.g., promotional materials, water spills, or misplaced boxes), and send camera-based alerts to store staff. It also helps you check if automatic doors work and open as expected. 

Outside the store, vision systems can analyze whether parking spaces are available or whether any vehicles block the shop entrance for a long time. They can continuously inspect the emergency exits and signal store staff if any obstacles are blocking the way. 

Final Thoughts

Once you’ve navigated to the end of this article, you might better understand how computer vision is adopted in different activities of retail stores. From automated inventory management and loss prevention to self-checkout systems and AR mirrors, this tech is changing the retail industry significantly. With these use cases, machine vision can boost in-store efficiency, reduce operational costs, and enhance customer experience. Considering this tech in your business strategies can give you a competitive edge in the retail industry. If you want to learn more about this amazing technology, subscribe to our blog and receive the latest news!

The post Computer Vision in Retail: Benefits & 10 Popular Use Cases appeared first on Designveloper.

So, are you finding a detailed source to learn about vision AI in industrial manufacturing? If so, this article is the right place to kickstart! Here, we’ll break down the definition, benefits, and popular use cases of this advanced technology in manufacturing. Ready to explore? Keep reading!

Understanding Computer Vision in Industrial Manufacturing

What is Computer Vision in Manufacturing?

In industrial settings, computer vision is a technology that enables specialized software (traditional or deep learning) to “see” and analyze visual data collected from manufacturing equipment. 

Particularly, cameras and other visual sensors are embedded into machinery to acquire images and videos of each product, material, or process. These images are then transmitted to specialized systems for real-time analytics. The systems here can be:

• Traditional software that uses explicitly programmed techniques (e.g., feature-based methods) and algorithms for basic tasks. Particularly, they check and analyze relevant features (e.g., edges, textures, or colors) against pre-established benchmarks to take simple actions like categorizing objects, processing images, or identifying defects. 

• Deep learning software that uses advanced algorithms and techniques (e.g., feature extraction or pattern matching) to automatically learn features from big data and deliver more accurate solutions. For this reason, vision systems using DL technologies can perform complex tasks like locating parts in cluttered environments, validating assembly, or inspecting character reading. 

With these capabilities, computer vision has wide adoption in industrial processes, from automotive and consumer electronics to textiles and pharmaceuticals.

Advantages of Machine Vision

Computer vision brings immense benefits to manufacturing. Here, we’ll elaborate on some of the key advantages of using vision systems in this industry:

Increase Quality Control & Defect Detection Rates

Computer vision helps your manufacturing plant detect flaws early by using cameras and machine learning algorithms to inspect products in real-time. The system can constantly monitor each product and process with the same focus and precision to catch even the smallest defects. This consistency ensures only high-quality products can leave the factory.

Improve Operational Efficiency

Computer vision helps your factory operate more efficiently by managing production lines continuously. If a machine slows down or a part is out of place, CV systems can immediately respond to the problem. This will decrease downtime and improve output. 

Similarly, through visual stimuli retrieved and analyzed by the systems, managers better understand how each part of the manufacturing process is working. This allows them to make instant adjustments to optimize the workflow.   

Cut Down on Waste & Production Costs

Computer vision can capture errors that might be hard to notice with the human eye. For this reason, each production step can meet exact specifications and maintain high accuracy. This will minimize the likelihood of materials being wasted on defective products. Less waste means saving more money on raw materials. Further, with real-time monitoring by machine vision, your manufacturing plant can lower the need for human inspection, hence reducing labor costs while maintaining high quality. 

Improve Safety

With vision systems, factory environments become much safer for human workers. By spotting potential hazards like a machine overheating, the systems can send an immediate alert. This enables human workers to take quick action and avoid unexpected accidents. Additionally, computer vision can monitor workers’ activities to ensure they’re adhering to safety requirements. This helps limit injuries and makes the workplace safer for everyone. 

Future of Machine Vision

These benefits have increased the demand for industrial machine vision systems across factories. Especially in sectors like automotive or electronics where minor defects can result in significant financial losses and reputational damage, using machine vision models for quality control and inspection is a must. Therefore, it’s no wonder that the global revenue of these models will witness a 7.21% annual growth rate from 2024 to 2031. 

AI advancements also open more avenues for industrial computer vision to thrive in the future. Deep learning algorithms, typically Convolutional Neural Networks (CNNs) can greatly improve image recognition. Advanced optics and imaging technologies, meanwhile, can detect subtle defects and inconsistencies that were previously hard to notice with the naked eye. Combined with high-resolution visual sensors, these technologies have helped manufacturers analyze images, make real-time decisions, and even conduct predictive maintenance more effectively. 

Top 10 Computer Vision Applications in Manufacturing

Realizing the huge potential of computer vision, more and more manufacturers have integrated this technology into their industrial processes. From automotive quality monitoring to electronics PCB (Printed Circuit Board) inspection, and beyond, its applications are diverse and vast. Below, we’ll detail the top ten ways machine vision is transforming production:

1. Quality Control & Inspection

Quality control and inspection are considered the key drivers behind the growth of computer vision in manufacturing. 

Vision systems, coupled with smart cameras and sensors, can catch images of each product item on the assembly line. They then use algorithms and techniques like image fusion or multiscale matrix fusion to compare these images against preset benchmarks. This helps them identify even tiny flaws that might be invisible to the human eye. These defects can be subtle misalignments, microscopic scratches, or minor color changes. 

In such industries as automotive or pharmaceuticals, all products must meet stringent standards before going to the market. With real-time analysis, manufacturers can modify and refine their processes or take informed action right away to increase overall quality. Therefore, more companies are investing in machine vision systems to automate quality control and inspection.

For example, the BWM Group’s plant in Dingolfing, Germany, developed an AI-powered vision system with infrared cameras to spot defects precisely within seconds. For example, it can identify minor cracks on flat sheet metal parts or missing model designations on vehicles.

2. Product Design, Modeling, and Simulation

Before being manufactured in factories, a product must go through the design, modeling, and simulation phase. 

One of the popular applications of computer vision in this stage is combining CAD (Computer-Aided Design) techniques to convert 2D images of existing products to 3D models. This process, also called “3D restructuring,” helps catch and display complex details or shapes that are difficult to measure manually. 

CV systems, accordingly, can use range data (“depth information”) from 2D images taken from different angles to build the 3D surface or geometry of an object. They can also create solid models from scanned data. 

These 3D models are then leveraged for prototyping products, undertaking downstream analysis, and understanding the position or orientation (pose) of an object in 3D space. Further, through CV-generated 3D models, you can simulate and validate how a product can look or perform in real-life environments. You accordingly can test different features like shapes, sizes, or materials without the need for building various physical prototypes. 

So, how does computer vision work in product design and modeling? Let’s take a look:

• First, cameras take live images of an object from different angles.
• Then, key features like edges or corners will be retrieved from each image.
• By matching these features across different images (e.g., the same edge of the object from many angles), the CV system can connect these identical points as well as estimate each camera’s position and angle when it took each picture.
• Designers then use camera positions to calculate the 3D location of those matched points and build a 3D surface for the object. 

3. Additive and CNC Manufacturing

Additive manufacturing (AM), also called 3D printing, is a process where manufacturers can add each material layer one by one until the final product is created. In AM manufacturing, computer vision supports a nesting process that involves organizing different parts (e.g., medical prosthetics) within a printing area to maximize space usage while reducing material waste. 

Particularly, CV algorithms analyze the shapes, sizes, and angles of those parts to optimize arrangement in a printer’s workspace. This helps fit as many parts as possible to prevent potential overlap while ensuring no empty spaces are left unused. For advanced setups, computer vision can adapt real-time nesting arrangements, like parts moving during printing.  

CNC (Computer Numerical Control) manufacturing, on the other hand, is a process where computer-controlled machines automate the production of components and parts. As such, it uses specialized computer programs to guide the movements of machine tools (e.g., welders or routers) to manufacture parts with high precision. 

So, how does computer vision assist this process? Using cameras or sensors to take live images of an object (like the golf-club head), a CV system then processes these images to identify the precise position and angle of the workpiece. If the object is incorrectly placed, the system can instruct a CNC machine or robot to modify the positioning for specific tasks (like welding). 

It then creates accurate paths based on the object’s shape. For example, to weld the golf-club head perfectly, the CV system uses the visual data to draw the optimal contours for the welding laser or torch to track. The system can constantly adjust the paths in real-time. 

4. Part Sorting & Tracking

This is a basic, yet crucial application of computer vision in manufacturing. Accordingly, CV systems can recognize, organize, and track parts when they move through the production process. 

By scanning barcodes, QR codes, or radio frequency identification (RFID) tags, vision systems can sort parts based on their shapes, sizes, colors, or markings. In advanced environments like automated warehouses, the systems can use algorithms like CNNs to identify high-quality and defective parts. 

Then, the systems can automatically route parts to the right place for further processing, assembly, or inventory without much human intervention. Therefore, your manufacturing staff doesn’t only ensure that each part is processed correctly and instantly but also tracks parts and their progress through different phases of production effectively. This is especially useful in industries with high risk like steel, where vision-based techniques can help handle the challenge of labeling and tracking steel materials with high temperatures. 

5. Assembly Line Automation 

Assembly is a crucial stage of the manufacturing process, especially for discrete industries like automobiles, aeroplanes, or smartphones. Today, to accelerate time to market while keeping product quality high, many manufacturers are investing in advanced technologies to automate part assembly.

One typical example is Tesla. In early 2024, the Tesla Manufacturing page posted a tweet with a short video to announce that Giga Shanghai automates 95% of its production process, from logistics and casting to paint and general assembly. This enables the factory to increase its annual capacity of vehicles significantly. With automation across the manufacturing process, Tesla Shanghai successfully produced one million vehicles in just 12 months, which previously took two and a half years to achieve. 

Giga Shanghai operates a 95% automated production line, enabling a cycle time of less than 40 seconds!
From taking 2.5 years for the first million cars to be produced, the second million was done in just 12 months 🚘🪄 pic.twitter.com/IF1w27AFPr

— Tesla Manufacturing (@gigafactories) January 5, 2024

Beyond automotive, CV systems combine human intelligence with the computer’s processing power for greater efficiency in other different industries. For example, they’re mainly used in assembling cabin products (like airplane cabins) and flexibly connecting cables onto hard disk drives in printed circuit board assembly. Additionally, vision systems help robots recognize, pick up, and place parts exactly in the exact positions to speed up assembly. 

Computer vision is also combined with augmented reality (AR) to make assembly operations more interactive. In particular, they identify a factory worker’s movements and guide the worker in real-time for mechanical assembly, like pointing out where each part goes. Especially in the case of assembling something with a lot of parts, like pieces of furniture in the figure below, some parts look too similar. This makes it tricky to know where these parts should fit together. 

Using just a single image, computer vision can predict the correct position of each part in 3D. It then sends this information to workers so they can know exactly where to put them appropriately. 

6. Robot Guidance

Companies, typically automakers and their suppliers, have used computer vision to help robots understand their surroundings and guide them in manufacturing tasks. These vision-guided robots (VGRs) are embedded with one or more cameras to send a feedback signal back to the robot controller for inspecting quality, identifying objects, and more.

For instance, Peterson Manufacturing – a global leader in producing wiring harness and lighting systems for vehicles – used Seiko Instruments’ VGRs to load parts onto its conveyor belt. The machine vision system helps the robots check whether the components are turned in the right direction before placing them on the assembly line.

Today, there are various approaches to robotic guidance and control. They include stereo vision, projected texture stereo vision, time of flight (ToF), photogrammetry, structured light, and more. Each method provides VGRs with different toolkits to perform production tasks. Stereo vision, for example, takes images from slightly different angles and compares these images to calculate the depth and generate a 3D view. With this capability, stereo vision is used when VGRs need to discern depth, like navigating around obstacles or collecting objects from a conveyor belt.

7. Predictive Maintenance

Machinery downtimes can result in significant losses. Therefore, computer vision, augmented with IoT and deep learning, is introduced to constantly track manufacturing equipment and warn engineers about early signs of issues like overheating. 

Cameras connected with a CV system are installed to continuously take live images of important components like belts, gears, or moving parts. The system is trained to distinguish normal operating conditions. So it can identify any deviations or anomalies, like minor cracks, unusual vibrations, or leaks, even when they’re invisible to the human eye. 

GE Aerospace – the world’s leading manufacturer of jet engines – has used the vision-based blade inspection tool (BIT) to routinely monitor engine blades that operate in the hot section of airplane engines. 

The BIT collects high-quality visual data from fixed-position cameras and groups the data together for operators to flag blades that need further inspection. Then, the tool will instantly measure the blades to see whether they have any defects. With AI assistance, the tool cuts down on the predictive maintenance time from 3 to 1.5 hours.

8. Operational Safety

In manufacturing environments, workers often confront deadly hazards, such as machine-related injuries, slips, or chemical exposure. Therefore, ensuring operational safety for workers is always one of the top priorities in this realm. 

Advanced technologies like vision AI are the key to this issue. Reinforced by deep learning algorithms and advanced techniques like YOLO models, computer vision can analyze visual data extracted from security cameras or other devices to identify objects or actions that could endanger workers. These hazards can be proximity to heavy machinery, the wrong use of personal protective equipment (PPE), unsafe postures, job-related stress, etc. 

Below is an example of how YOLO models use computer vision to classify whether workers are present in a dangerous area and whether they wear PPE as required:

Understanding the growing importance of operational safety, various companies have provided CV-powered platforms to monitor worker activity and working sites. Some common tools include TuMeke, Cipia, and Microsoft’s Azure Video Analyzer.

9. Packaging

Computer vision boosts the accuracy and efficiency of packaging. By identifying the position and direction of products on the conveyor belt, a CV system can learn whether they’re correctly aligned for packaging. Accordingly, when a product is upside down, the system can tell robots to adjust it. 

Moreover, vision systems can ensure the quality of packaging by checking for defects like poorly sealed packages, damaged boxes, or incorrect labeling. If the packaging doesn’t meet quality standards, the systems can alert manufacturers to remove defective products, hence preventing costly recalls and customer dissatisfaction. 

Machine vision systems also automatically count and sort products that need packaging. They ensure each batch has the correct quantity. This helps avoid waste and improve consistency.

One successful example of using CV systems in packaging is P&G (Mumbai, India). The company had a high volume of detergent packing lines with similar packing laminate sizes and colors. The risk of errors was high, particularly with packing products in the wrong laminate and printing the wrong MRPs (Maximum Retail Prices). This resulted in expensive repacking and pricing issues. 

To solve these problems, P&G incorporated Cognex In-Sight® vision systems that use OCV (Optical Character Verification) and the PathMax algorithm for checking packaging in real-time. This integration removed manual inspection and increased packing accuracy.

10. Transportation

In manufacturing, transportation activities can involve delivering materials within a workshop or processing logistics between factories. 

In a plant setting, various manufacturers are using AGVs (Automated Guided Vehicles) that work thanks to a navigation system, a power system, and a control system. Unlike traditional AGVs that run along marked lines on floors, modern AGVs use computer vision to capture more advanced navigation signals like images, radio, or lasers. This tech helps them find the best route and avoid obstacles.  

Toyota, for example, has implemented AGVs since 2019 for a safer work environment and smoother flow. Particularly, the brand has used an automated TAE500 tow tractor to transport components in the welding shop and SAE stacker trucks to move pallets from the conveyors to a storage area.

In logistics, CV is also used by large-size autonomous vehicles like logistics or forklift trucks to deliver goods between different factories. Using advanced algorithms like the covariance matrix, CV helps these vehicles identify and track moving objects. This makes transportation safer and more efficient.

Barriers to Computer Vision Adoption

We can’t deny the high application of computer vision across manufacturing processes, plus its huge advantages. However, we’re also witnessing visible constraints on adopting this technology widely: 

High Initial Costs

Installing industrial machine vision systems requires a significant upfront investment. It covers hardware (high-resolution cameras, powerful processors, and advanced lighting) and specialized software. Not to mention that customizing apps for your specific needs or integrating the systems into your current workflow can add up expenses. 

This raises a big question: are the benefits of computer vision worth the high initial costs? The answer depends on each manufacturer. But for small and medium-sized businesses, these costs might become a substantial financial burden and need careful consideration. 

Data Privacy and Security Concerns

CV systems often harness large volumes of visual data from production lines and machinery. For various manufacturers, this data is sensitive and crucial. They’re worried about possible attacks that may reveal proprietary information, manufacturing processes, and strategic insights. This concern grows bigger when their factories use network-connected or cloud-based systems. 

Moreover, some specific industries like healthcare and pharmaceuticals are under stringent regulations (e.g., HIPAA). Using unapproved vision systems may expose your manufacturers to regulatory violations, consequently leading to financial or even legal penalties. 

Complexity of Integration

Integrating computer vision systems into your manufacturing plant is complex due to its technical challenges. First, machine vision systems combine a range of hardware and software, often requiring significant adjustments to be seamlessly compatible with your existing infrastructure. Second, the complexity can come from the demand for aligning cameras accurately, tailoring software, and calibrating imaging systems. 

Skills Gap & Expertise Shortage

Implementing vision systems requires technical knowledge and specialized skills. They may involve expertise in machine learning, deep learning, and data analytics, as well as an understanding of certain industrial processes. This poses a real challenge if your business lacks access to the right experts. 

The only solution to this problem is investment in training your existing employees or recruiting new professionals. Training in-house teams requires costs and time. Meanwhile, partnering with third-party experts may create a growing dependence and even increase costs over time.

Transform Your Manufacturing Operations With Designveloper

You’ve discovered all the essentials of computer vision in manufacturing, plus its important applications. Empowered by technological advancements like IoT or deep learning, computer vision will likely have a higher application in the future. 

At Designveloper, we understand the power of computer vision for quality control and production efficiency. With our extensive expertise, we assist you in seamlessly integrating this technology into manufacturing operations. We promise to craft robust, scalable solutions that exactly fit your specific needs. 

One of our successful projects is to help a leading electronics manufacturer reduce defects by 40% and lower inspection costs by 25% with the custom integration of computer vision. Further, we also provide end-to-end support, from planning to full deployment and ongoing maintenance, within your budget.

So why wait? Partnering with Designveloper today to revolutionize your manufacturing process. Contact us and discuss your idea further!

The post Computer Vision in Manufacturing: Basics & 10 Applications appeared first on Designveloper.

What Are the Agile Principles?

We all know Agile means moving and thinking fast and easily. Based on that concept, the Agile model was introduced, especially in the software industry, to facilitate and improve project management.

Right from the beginning, experts developed the Agile principles to help teams learn to use agile methods. Particularly, in February 2001, a group of experts from different tech subsegments met by chance in the Wasatch Range of Utah.

Confronting the so-called shortage of a standard mindset for software development, they built the Agile Manifesto that covers 12 agile principles. These principles, in other words, support tech specialists to think about projects and software development in an agile way.

Now, let’s take a deep look at each of them:

Agile Principle 1

“Our highest priority is to satisfy the customer through early and continuous delivery of valuable software.”

To make a product quickly delivered to end-users. Agile teams often focus on creating a minimum viable product (MVP). An MVP only comes with enough core features and is often used by early real customers. They accordingly give development teams early feedback about the software for continuous improvements in the future. 

So no matter whether your team wants to build an MVP or release improved features. The highest priority is always making your customers happy about the values they receive from software. 

How it works in practice:

• Develop an MVP to test your paper ideas;
• Regularly release updated versions and features to constantly promote the feedback loop between end-users and products;
• Make continuous improvements based on market trends and customer responses.

Agile Principle 2

“Welcome changing requirements, even late in development. Agile processes harness change for the customer’s competitive advantage.”

In some industries like IT, the market and customer demands are usually changing. Accordingly, a product that is developed with well-documented plans doesn’t always meet changeable needs. Therefore, agile comes into play to help resolve such a problem.

Particularly, agile processes enable product teams to respond to changing market trends, user demands, and even competitive threats with ease. Teams then can review, analyze, and add new findings when necessary to build a more satisfying and competitive product. 

How it works in practice:

• Agile teams don’t work based on a predetermined set of features, but rather high-level strategic objectives. These goals support them in building coherent products that respond well to market changes.
• Changes in market and customer needs are among the main drivers behind product improvements. Agile teams frequently modify plans sensibly to best serve such demands.
• Also, those adjusted strategies also need to suit business requirements and expectations. So product owners and other stakeholders should understand well why changes in products are essential.

Agile Principle 3

“Deliver working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale.”

Agile allows development teams to shorten the time from ideating to releasing a product. To do so, agile teams repetitively conduct, deploy, and modify a product’s functionality in short cycles instead of building the entire software. In other words, agile teams focus on creating and shipping some small parts of the software. 

This property helps set agile apart from traditional approaches which come with long development phases. Further, it gives your team more avenues to continuously validate hypotheses and ideas. 

How it works in practice:

• Teams break software development activities down into smaller pieces. They will complete such activities that are completed in a short timeframe called “iteration”. An iteration typically lasts two weeks. But in reality, it still depends on the project’s complexity and size as well as your team’s velocity.

Agile Principle 4

“Business people and developers must work together daily throughout the project.”

The agile model requires frequent interactions between a client (commonly known as “a product owner”) and developers. 

As small chunks of work are conducted in short-term cycles and changes can be made, the presence of business representatives is necessary. This is because a successful product needs to be examined not only from technical aspects but also from business insights. 

Therefore, frequent communication between product owners and development teams prevents misunderstanding and builds transparency and trust. Also, working together throughout the project helps ensure work progress and a product’s quality. 

So how can this meeting be conducted? At Designveloper, for example, our team often holds a sync-up meeting that last around 15 minutes per day to get an overview of the task status and any difficulties encountered. This helps our team quickly address any challenges hindering software development.

How it works in practice:

• Besides those taking over development tasks, a multidisciplinary agile team also includes a product owner and other stakeholders who cover business aspects.
• Regular meetings are held to keep people constantly involved in product development and update procedures.

Agile Principle 5

“Build projects around motivated individuals. Give them the environment and support they need, and trust them to get the job done.”

Agile itself has cons. Many companies, however, tackle its drawbacks and still succeed in creating the desired software by building a strong core team. 

Accordingly, an agile team needs motivated individuals who have decent leadership skills and proper expertise to do jobs well. Also, team members should be given autonomy, a reliable working environment, and obviously defined responsibilities before projects start. 

How it works in practice:

• A product owner needs to explain requirements and devise a clear roadmap for a development team to understand. 
• Meanwhile, development team members interpret how to build a product’s components. Particularly, they are in charge of developing UX/UI design and backend. 

Agile Principle 6

“The most efficient and effective method of conveying information to and within a development team is face-to-face conversation.”

There’s a wide argument that face-to-face meetings are the best way to exchange information. Although this statement holds true to some extent, it’s not always possible for product owners and developers to meet in person. Especially today, many companies tend to use offshore outsourcing services. So most conversations now take place online (typically video conferencing). 

Regardless of communication channels, the key meaning behind this principle is always motivating members to interact about software, strategies, and requirements in real-time. 

How it looks in practice:

• Daily stand-up meetings;
• Iteration planning meetings;
• Frequent backlog grooming;
• Pair-programming sessions;
• Regular demos.

Agile Principle 7

“Working software is the primary measure of progress.”

There’s perfect software, as the market is always changing and customers often alter their demands. Therefore, instead of depending on detailed plans and documents to build a so-called perfect product, you should focus on a working one. 

The working software doesn’t only operate on your expected platforms and devices but also meet user and business requirements. Teams often release updated features to provide customers with useful values. 

How it works in practice:

• Development teams prioritize the development of minimum viable components for an MVP to get quick feedback from the first real customers. 
• Teams apply the fail-fast technique to experiment with ideas quickly while trying to achieve expected outcomes.
• Teams try to build a useful product rather than a perfect one by frequently shipping new releases. 

Agile Principle 8

“Agile processes promote sustainable development. The sponsors, developers, and users should be able to maintain a constant pace indefinitely.”

As said before, agile processes enable product teams to build and deploy new features continuously. This encourages a product’s sustainable development. 

However, updating versions too often and too rapidly may exhaust team members, especially if they set too high goals. To avoid exhaustion and turnover, a cross-functional team should establish realistic expectations, learn to stay enthusiastic, and enhance work/life balance.

How it looks in practice:

• Team members determine how much work needs to be done before each iteration. The workload depends on the capacity and velocity of developers as well as a timeframe. So they should not exaggerate what they hardly do.
• Agile teams should identify which tasks to do during each iteration. No responsibility is added if cases are irresistible. 
• A product owner should create an atmosphere of mutual trust with developers that allows free feedback and open communication. 
• A product manager or a Scrum master should function as a mediator. He/She needs to avoid unplanned activities over an iteration and curb the superfluous intervention of a product owner in technical jobs. 

Agile Principle 9

“Continuous attention to technical excellence and good design enhances agility.”

As we’re talking about building software, its technical components and design are what you should care about. During the agile development process, frequent releases and updates are encouraged but with consideration. In other words, agile teams should attend to developing intuitive interfaces and free-bug codes to avoid unexpected troubles induced by poor technical performance.  

How it works in practice:

• Agile teams distribute development resources to code refactoring. This technique helps modify the software’s internal structure but does not affect its functional attributes.
• Technical debt is the hidden cost of leaving some functionality for later development to focus on speedy delivery instead. A product owner and developers should discuss the software’s tech debt impacts to grasp when or whether such costs are acceptable. 

Agile Principle 10

“Simplicity–the art of maximizing the amount of work not done–is essential.”

For rapid shipping, the agile approach highlights the importance of simplifying the first version of a product. 

Simplicity here means minimizing the amount of work done but still achieving the most optimal results. Like the Pareto principle, 80% of a team’s desired outcomes come from 20% of development work. 

Accordingly, team members need to work on the most influential features that prioritize solving the pain points of users and reaching organizational goals. Building an entire complicated product also proves redundant during the agile development process. 

How it works in practice:

• A product manager uses agile prioritization models to carefully pick which features or user stories should be included in the software. Also, such attributes and development strategies need to be closely aligned with business goals. 
• Short iterations of agile allow your team to experiment and validate your ideas quickly. This accordingly helps discover good initiatives and filter out bad ones. 

Agile Principle 11

“The best architectures, requirements, and designs emerge from self-organizing teams.”

The agile methodology is closely linked to the key principle of encouraging individuals to work together in a “flat” working environment. It’s where team members contribute opinions and then a whole team finalizes decisions rather than a managerial individual. This concept helps boost a group’s communication and values over the software development procedure. Besides, a self-organizing team can create the best designs and functionality for a product.

How it works in practice:

• Different companies build self-organizing teams in different ways to carry out respective projects. These groups are given autonomy to take over the right responsibilities. Then control the whole process and make product-driven decisions.

Agile Principle 12

“At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behavior accordingly.”

The agile model ties to the idea of continuous improvements. This concept is not only about the way you release new updates to reflect on the changing market and improve the software. But it also extends to development procedures and teams. In other words, your team should learn to become more productive and enhance processes.

How it works in practice:

• Your team needs to revise and test not only products but also the development process and working style. Evaluating and adjusting the development method is essential to ensure it supports software-building activities effectively. 
• Frequent retrospectives are occasions for your team to discuss what was done well in a previous phase and what needs to be improved in upcoming phases. It helps reflect on how parties communicate and whether developers were given what they need to complete tasks well. Accordingly, all parties can adjust their working strategies and behaviors to work more effectively next time.

Designveloper hopes that the 12 agile principles above can help you work more smoothly than before! For more interesting articles about Agile methodologies, subscribe to our blog today!

The post 12 Agile Principles and How It Looks in Practice appeared first on Designveloper.

A genuine software development company would know the method by heart since the top priority is their customer’s interest. This is exactly what is Agile software development method concentrates on.

What is Agile Software Development?

Agile is a set of frameworks and development practices in the approach of software development with a heavy emphasis on the importance of the human factor.

Instead of focusing on the development of an entire product, Agile prioritizes the most important features of the product. Through real-life feedback from stakeholders and market shifts, a development team continues to improve the product so that it can meet evolving demands. This focus on human collaboration sets Agile apart from other software  methodologies like Waterfall.

At Designveloper, we’ve applied Agile software development approaches, typically SCRUM and Kanban, to all projects. Below is Designveloper’s workshop that elaborates on the basics of these Agile frameworks.

1. Agile software development life cycle (SDLC) model

Agile SDLC takes a developer through six basic stages of a typical project. They include planning, analysis, design, implementation, testing and integration, and maintenance. These stages are repeated in cycles (known as “sprints”) to continuously modify and improve the software. Each sprint often lasts two weeks, so developers need to estimate the right number of tasks, coupled with their assigned time and resources, in each sprint. This ensures adaptability to change during development. 

2. Case study: Instagram and Designveloper

There are various businesses shifting from traditional software development approaches to Agile and acquiring a big success. This has encouraged more and more companies to gradually adopt this approach to different aspects of their business operations. Understanding this need, the global value of enterprise agile transformation services is expected to grow by roughly 17% from 2025 to 2033. So, how can Agile bring success to Let’s take a deeper look at two prominent case studies. 

Instagram

In the stage of sketching a brand new product, Instagram’s team leaned on the efficiency of the Waterfall model. Having tested the mobile app with real users, gained feedback from the user experience. The team used the Agile method to make quick modifications like cutting down unnecessary. Or adding more features based on the user inputs.

By doing this, the team was able to deliver what customers really want as opposed to what they thought the customers would want. After applying Agile in the building and testing the product one more time. The mobile app got its debut and the rest is history.

Success: Agile led Instagram to a million downloads within two months of the mobile application’s launching.

Designveloper

Designveloper teams have adopted Agile for a long time, particularly following the SCRUM framework in the Agile methodology. When we worked on the Lumin PDF project, we needed to rebrand almost 50 static web pages of the Lumin website. Initially, we adopted a linear approach where we designed, developed, and tested each part of the project when we went along. 

However, this approach presented some challenges. Typically, when the team was working on page 20 and received feedback for page 1, we would have to go back to adjust the design and documentation before reupdating it on the development environment. This led to significant delays due to rework.  

That’s why we made a change to the Agile methodology and divided our work into small, manageable tasks needed to be done in each sprint. This gave us a clear view of the work ahead and any difficulties we might encounter. 

Success: Our team worked more productively and reduced the time spent redoing finished tasks. This ensured timely delivery within our client’s expected budget.

3. The roles of people in an Agile team

If the Agile approach was so praised by companies whose software development projects proved the success of the development methodology, then how should you as a business owner implement this approach and how can you structure your organization for the new project? 

In a human-centric manifesto like Agile, there is no heavy sense of hierarchy as elements like human interaction, communication, and teamwork are valuable over the order of an organization. Since the approach is big on adaptability and customers’ feedback, the role of testers is the most important since the product’s success is without customers’ actual needs and demands. 

5. Agile work process

The work process in the Agile software development approach goes through basic steps from research, estimation, quality assurance, development, design, prototyping, and launching. Each business aims at a different specific feature of the project. 

If projects depend heavily on research and development (R&D), for example, understanding the market and customer demands often evolves alongside the project itself instead of being fully defined from the beginning. Through activities like market research, customer survey, and discovery, the development team can get insights that allow the project to adapt to evolving client requirements. 

If your business is all about the best quality a product can offer the market, the steps of quality assurance, quality control, and customer support would be of vitality since top quality is purely decided by product users. To each their own, each business needs to determine the top priority of their project outcome and discuss it with developers as communication is the key topic of Agile.

Agile Manifesto and Its 12 Core Principles

The Agile Manifesto is at the core of the Agile Movement. It was born in the 1990s to bridge the gap between business requirements and the final delivery of a product. The Agile Manifesto emphasizes lean manufacturing, human interaction, collaboration, and constant improvement. In other words, it ensures seamless communication, swift development, and adaptability to external factors while maintaining the core track of the plan.

The Agile Manifesto has the following 12 core principles a developer must bear in mind at all times while applying Agile:

Agile’s 4 Core Values for Customer-Centric Businesses

In addition to those core principles, you should understand four Agile core values as follows if you want to create a customer-centric product.

1. Human over tools

The first value in the Agile Manifesto is human over tools. The human factor wins over other elements like processes and tools as it is the people who directly respond to business requirements, such as the features a client required.

Based on understanding initial requirements and the client’s specific industry, the development team then can decide which tools or development processes to adopt. This ensures the team can develop a custom product that aligns with the client’s business.

2. Working software over documentation

The second value is working software over documentation. Data input requires time, discipline, and meticulousness, which only the human factor can do. However, Agile does not completely wipe out the element of comprehensive documentation. But it allows developers to get in closer touch with the piece of information without the burden of processing and data input.

3. Customer collaboration vs. term negotiation

Human interaction plays a key role in the Agile software development method, especially when customer needs grow.

To collaborate effectively with a client, your development team needs to establish a clear and open communication channels. These channels help the client and the whole team keep up with the progress, exchange ideas or feedback. This not only leads to better outcomes but also forges the long-term relationship with clientele.

Further, to ensure transparency and clarify collaboration methods, it’s crucial to negotiate detailed partnership contracts or documentation.

4. Instant response and adaptability to the original plan

Adaptability can be highly valued in the Agile Manifesto. Swift responses to customers’ feedback and the latest changes in market insights usually would drive the working process further from the original plan.

This means, as opposed to rigidly sticking to the initial execution plan, Agile adapters would listen to the external environment and create changes accordingly without altering the original mission statement of the overall plan.

Developers, meanwhile, should keep in mind that there is more than one way of achieving one specific goal. It is completely okay to abandon a no-longer A-okay plan to pursue something new, especially when this answers well to the market and retains your business’ credibility to the users.

Advantages vs. Downsides

Conclusion

With all what we analyzed, you might better understand what Agile methodologies are and how they benefit your software development. Having said that, it still comes with several shortcomings and cannot be useful in all cases. If your project aims at adapting quickly to market shifts or customer demands, Agile can be a good choice. So, consider your business’s project requirements, specific industry, and end-users before going to the final decision on whether to adopt Agile. For more interesting topics about this development methodology, subscribe to our blog!

The post What is Agile Software Development? appeared first on Designveloper.

In this post, we’ll talk about what Java is and its usages. We’ll also show you some real-world programs written in Java. So, let’s head into it.

What Is Java?

Java is a high-level programming language that is cross-platform, object-oriented, and network-centric. It has been a popular choice for developers for almost twenty years, and millions of apps are now being used that were written in Java. It is a programming language Java will help code everything from mobile apps and business software to big data applications and server-side technologies because it is fast, safe, and reliable.

It is one of the most popular programming languages around the world, with 30.3% of software developers using it as of 2024. This is because it is open-source and compatible with any operating system, following the “Write Once, Run Anywhere.” philosophy.

It should depend on the implementation as little as is humanly possible. A programming language made for developers that lets them write code only once and then run it everywhere.

Any platform that supports Java can run code that was written in Java. Java programs are turned into something called “byte code,” which can run on any Java Virtual Machine. The syntax of Java is similar to that of C and C++.

Recommended reading: Best Javascript Tutorial for Beginners in 2023

History

Java is a type of computer language that was made for the first time in 1991. In 1991, a group of Sun developers called the “Green team” made the first version of the Java programming language. In this group were James Gosling, Mike Sheridan, and Patrick Naughton. Sun Microsystems released the first version of Java to the public in 1996. This version was Java 1.0. It gives away free runtimes for many popular systems. Arthur Van Hoff rewrote the Java 1.0 compiler from scratch in Java so that it meets all of the standards. When Java 2 came out, new versions came with a number of pre-built configurations that worked best on certain platforms.

In 2007, Sun released Java under the GNU General Public License, which made it completely open-source. When Oracle Corporation bought Sun Microsystems in 2010, the company took over control of the Java programming language.

5 Reasons To Learn Java

If you learn Java programming, you might be a better candidate for jobs that require computer programming skills. There are also the following benefits, which might prove Java’s worth. 

1. Ease Of Use

Java makes programming easier because it takes away some of the complexity that is in a lot of other programming languages. Some of these problems are operator overloading and pointers, to name just a couple. It was meant to be a strong, advanced language that was easy to use and understand. It was based on C++.

2. A Great Starting Point

Once you know Java well, it shouldn’t be too hard to learn other programming languages like C, C#, C++, Python, and others. Beginner programmers can learn how to think like experienced programmers by using Java, which guides them through procedures using logic and tests their ideas.

3. Portability

Java programs can run on almost any computer that has the ability to install a Java Runtime Environment (JRE). This quality, which is sometimes called “platform independence,” lets the source code work on almost any network, server, and client.

4. Performance & Security

Java’s all-terrain design means that its programs and scripts can run faster, make better use of their resources, and test any kind of code in a safe environment. In the most recent versions of the language, there has been a lot of focus on making sure the platform has strong code with reliable ways to find errors and threats.

5. High Earnings

As of 2024, Java, along with JavaScript and Python, becomes the top programming language demanded by recruiters (~40%). Over the next ten years, the number of jobs for software developers by estimations will grow by 22%, with backend developers in particular being in high demand due to the specialized skills they bring to the table. In the United States, wages for Java developers vary from $99,000 to $143,000 per year, with a typical income of $118,016, a fantastic number.

5 Applications Of Java

Java is an open-source programming language that is easy to use and understand. It is also stable, fast, scalable, secure, and doesn’t depend on a specific platform. It is also very flexible, which means the user can use it for a wide range of projects. What can you make with this widely used programming language?

1. Video Games

Java, which is the programming language behind games like Minecraft, is a good choice for making video games, especially ones on Android-powered mobile devices. Because of how well the language works, these kinds of applications can run very smoothly on these kinds of platforms. It can also add three-dimensional graphics to games with the help of jMonkeyEngine, which is open-source software. In addition, it is an excellent language for making 2D games.

2. Big Data Tech

Big data is a topic that is getting a lot of attention and activity in the software industry right now. It is the process of analyzing and getting information from large data sets in a methodical way. Hadoop is an open source platform for processing data that is related to “big data” made up of only Java. Java is better than other technologies because it has features like garbage collection, memory distribution, and a stack supply system. It seems likely that big data will move in the direction of Java in the future.

3. Internet Of Things (IOT)

When you use Java with other technologies, like artificial intelligence (AI), you may be able to power devices from afar, connect appliances and other items, and do a lot more. For example, you can start your slow cooker or change the temperature of your thermostat from far away using an app on your cell phone. The Internet of Things also affects a wide range of businesses, including healthcare, security, utility management, and supply chain management, among others.

4. Mobile Apps

Java has been widely adopted for Android app development, not only for the front end but also for the back end. Coupled with powerful libraries and frameworks like Spring, Java provides a robust and versatile platform to develop complex apps.

For example, at Designveloper, we use Retrofit – an HTTP client library – to help Android applications communicate with RESTful APIs. It offers a flexible and convenient way to create network requests and process responses by leveraging Java annotations and a declarative syntax.

Besides these powerful tech stacks, Java stands out among the different programming languages like Kotlin for other reasons, including its platform compatibility and a large group of users who support it. Further, Android Studio supports the programming language, which makes it possible to make a wide range of safe and useful apps for mobile devices.

Recommended reading: Top 5 Javascript Frameworks That You Should Master

5. Cloud Computing

WORA is another name for Java, which stands for “Write Once, Run Anywhere.” Because of this, this programming language is perfect for cloud-based applications. Cloud providers use Java as their main programming language because it can run applications on a wide range of systems. This is because of things like how well it works, how easy to expand it, and how reliable it is. In fact, many of the most successful companies in the world use Java to build their cloud apps. It was used to make Gmail, which is an example of a program that runs in the cloud.

5 Companies That Use Java

Various businesses use Java as part of their technology stacks. Below are five typical companies leveraging this programming language for their websites and apps.

Recommended reading: Why Learning Javascript Helps You Make a Lot of Money

1. Netflix

Netflix is one of the biggest and most well-known entertainment companies in the U.S. Through streaming media, the company sells movies and TV shows which you can watch online. Java is present n almost all of Netflix’s apps, especially for running the backend.

2. Spotify

Java is used to run Spotify’s web application, as well as to log, stabilize, and send data. Spotify is one of the most popular ways to listen to music online. It is the primary language of the Android app for Spotify.

3. LinkedIn

For LinkedIn, C++ is used for some parts of the app, but Java is used for most of the development. Java’s implementation is a big help to LinkedIn’s search and analytics features. To be more specific, it solves scaling problems, which in turn lets the server work faster while using fewer resources.

4. eBay

Over the last 27 years, eBay has always been ranked as one of the most successful online businesses in the United States. The back end of eBay is run by a set of Java technologies and in the Java virtual machine. Java is a great programming language for the platform because it can grow and stay the same.

5. Uber

Uber is the best example of how well Java works with other things. The company has to deal with a lot of real-time data because it has to keep track of its drivers and respond to trip requests as they come in. With this information, Uber should be able to quickly sort through the data and find users who are a good match. Java comes in handy here because it can handle requests and move data as quickly as possible.

Recommended reading: Top 5 Best Resources to Learn Vue.JS

10 Resources For Learning Java

When you first start learning Java, you may find that there are a lot of online resources for both new and advanced students that you can choose from. We’ve taken it upon ourselves to put together a list of what we think are the best resources for learning Java.

1. Coursera

Coursera is one of the most popular places to look for online courses, and Java programming is no exception. You can watch instructional videos there in English, Spanish, Russian, Chinese, and French, among other languages, with a subtitles option. You can learn the basics of Java there, as well as Java for Android and more advanced levels.

2. Udemy

This is another well-known website for learning Java and programming. It has both free and paid courses, but the good thing is that you have a lot to choose from and the costs aren’t too high. More specifically, there are many free courses in both Java and programming. This makes it one of the best places online to find free Java classes.

3. Educative

Another great website for beginners and people who learn best via interactive learning. You can use Educative without installing any software or going through any kind of setup because it lets you code online in your browser. This is very important because most beginners give up during the installation process. Educative’s text-based, interactive courses, quizzes, and tests can help you become an expert in any kind of technological skill. Java is one of these.

4. Codecademy

Beginner programmers can get a free introduction to Java programming on Codecademy. This lets them learn the basics of this programming language and work on seven different projects, like making their own calculator. The course will cover programming in general, as well as data structures, object-oriented programming, conditionals, and control flow.

5. Oracle Java Tutorials

Oracle, a global leader in software development, has made a free online version of the Java programming language’s basics curriculum. This tutorial contains regular updates and shows you how to build apps in a way that is simple and easy to understand. In addition to the basics, you will learn what a graphical user interface (GUI) is and how to build one. You will also learn more about custom networking and JavaBeans.

6. Sololearn

Sololearn made available a Java education course that you can take online for free. There are a total of 65 lessons in their curriculum, which consists of 6 different modules. You will learn about iterations and conditionals, arrays, classes and objects, exceptions, lists, threads, and files, among other things.

7. Codementor

Codementor’s collection teaches developers how to use Java online. It has not only lessons and courses, but also tips and suggestions that can be useful. Here, you can find all the latest news about Java, as well as articles and exercises about how to code. Do you also need some tools for building? You’re going in the right direction.

8. Pluralsight

Pluralsight has a lot of useful courses for people who want to learn Java and code online. You can study at your own pace and pick the classes that interest you the most. The site also gives you a 10-day free trial, which is more than enough time for usage.

9. edX

Some of the well-known schools that offer free Java classes through edX are the Massachusetts Institute of Technology (MIT), the Hong Kong University of Science and Technology, and the University of California, Santa Cruz (UC3M). There is no need to wait to sign up because most of the classes can be done at the student’s own pace. Also, when the course is over, you have the option of buying a certificate at your own cost.

10. Skillshare

Skillshare is a website where people who want to learn how to code can take free lessons in a number of programming languages, including Java. If you only have a short amount of time, you can sort the lessons by length and pick the shortest ones. This website also shows how many students enroll for a certain course and how they feel about it. Deciding which lessons to watch and whether or not they are worth watching is quite easy with Skillshare.

Conclusion

Java is the most popular programming language for making software all over the world, and for a good reason. If you’re thinking about making your own Java app and want to learn more about how to do it, this article could be a great place to start.

However,  if you’re stuck and need some guidance, don’t be afraid to contact us. At Designveloper, we have a team of experienced Java developers who are always available to help and come up with smart web development solutions.

The post What Is Java: Definitions, Applications & Learning Resources appeared first on Designveloper.