Unlocking the Potential of Computer Vision for Manufacturing Businesses

Unlocking the Potential of Computer Vision for Manufacturing Businesses

With over 16% contribution to global GDP, the manufacturing industry continues to grow while acknowledging rapid technological advancements. Disruptive technologies such as AI and data analytics combined with IoT are introducing automation to...

With over 16% contribution to global GDP, the manufacturing industry continues to grow while acknowledging rapid technological advancements. Disruptive technologies such as AI and data analytics combined with IoT are introducing automation to major manufacturing facilities. Under AI development services, applications of computer vision for manufacturing plants extend from quality inspection to inventory management and safety compliance.

This blog post explores effective use cases of computer vision technology across small and large scale production lines.

Quality and Packaging Inspection
Quality control is an essential business principle for every manufacturing organization. However, it is challenging for SMBs to bear the high operational costs and labor associated with quality control measures.

Emerging technologies such as IoT and AI are demonstrating high-end capabilities for automating the traditional quality control practices. Mckinsey’s lab research reveals that AI-powered IoT devices will raise manufacturing productivity and product quality by almost 20%.

The algorithmic advancements in AI’s computer vision technology are entering quality control facilities with more efficient and cost-effective solutions, such as-

a) Analyzing visual imagery with convolutional neural networks (CNN), a regularized version of multilayer perceptrons, that enable accurate identification of defected products.

computer vision cnn image processing

A look at the hidden layers of a CNN model.

b) Automation in packaging has opened the path for computer vision algorithms to supervise the standard quantity and methodology over packaging lines.

c) Automated defect inspection using pattern matching algorithms is replacing manual labor at electronics part manufacturing, medicine, and agricultural yield inspection.

How does Oodles AI use computer vision to automate quality inspection facilities?
We, at Oodles, have working knowledge of computer vision technologies to build real-time video surveillance systems. We use CNN and histogram of oriented gradients (HOG) to automate manufacturing processes in the following manner-

a) Our deep video analytics detect anomalies over production lines and raise an alarm during quality inspection. We have achieved over 80% accuracy in detecting defected products while maintaining speed.

b) After identifying differences, our model automatically saves the images and video frames inside the system for further training purposes. It leads to the comprehensive training of ML models that accelerate production and derive better returns.

Product Assembly and Safety Compliance
Workforce and data security is a major concern for manufacturing businesses. According to the International Labor Organization, over 2.3 million workers die every year due to occupational accidents or work-related diseases.

Computer vision techniques have already automated the inspection of basic product standards such as seal closure, position, labeling, and print quality. The future applications of computer vision techniques to ensure product compliance and workplace safety will witness the following developments-

a) Video Surveillance in-built with image processing techniques will enable businesses to track employee movements and with greater precision and associated data.

b) Optical character recognition (OCR) systems can sift through date codes, lot code, and expiration date to identify differences accurately. Also, OCR is efficient at tracking complete production cycles from raw materials to packaging lines.

c) Also, the integration of artificial intelligence services in sensor-based IoT devices can detect the overheating of machines well before the condition aggravates. Data from powerhouses such as voltage and tension can be used by computer vision techniques to predict short circuits.

Unlocking Computer Vision for Manufacturing Businesses with Oodles AI
The AI team at Oodles uses large machine learning (ML) libraries such as OpenCV and TensorFlow to train ML models. With OCR, real-time video analysis, object detection, and other computer vision techniques, we ensure safety for manufacturing in the following ways-

a) Our computer vision capabilities are efficient at mapping real-time employee and product positions to identify anomalies.

b) We use OCR systems to monitor complex product operations and details such as batch number, manufacturing details, expiration date, and more.

Talk to our AI development team to know more about our Computer Vision Services.

Is Low-code or no-code development is future of mobile app development

Is Low-code or no-code development is future of mobile app development

Mobile app development has skyrocketed over these years with the increasing demand of mobile apps for a variety of purposes like entertainment, banking, weather update, health, booking movie tickets, booking a taxi etc. With the latest...

Mobile app development has skyrocketed over these years with the increasing demand of mobile apps for a variety of purposes like entertainment, banking, weather update, health, booking movie tickets, booking a taxi etc. With the latest technologies adopted by mobile app development services, there are different app development approaches which are being practiced. Among them is low-code or no-code development. But will it be the future of mobile app development? Will any mobile application development company start taking this approach as the primary one. Let’s try to find a detailed answer to this question.

But first, let’s understand what this approach exactly is? Well, it is a streamlined approach which involves swift design as well as development with minimal coding, generally relying on different third-party APIs.

Even though there isn’t any single definition of no-code or low-code development because it is actually more of a mindset rather than something which can be directly measured, this mindset has certainly led to a vast community mushrooming up with this mentality. Android app development services are rapidly adopted by this approach. Low-code app innovators are rapidly disrupting all types of various industries. There are a plethora of benefits to these low code platforms and let’s look at this.

1. Less Number of Bugs

It is pretty evident that less code actually means fewer bugs. As simple as that. The entire bug testing phase is actually a major part of modern and latest application development. It is quite inevitable that various issues will come up if there is actually enough code present there. But the best thing regarding low code platforms is that there’s certainly less to test. Also, when they actually tap into APIs, those particular APIs are actually tested by other people.

Lesser number of bugs is better for both users, as well as developers since less amount of time, will be taken up with bug-fixes and troubleshooting. Also, the fast pace of this development approach actually means that if in any case a bug is found, it is generally better just to develop a new iteration rather than fixing it.

2. Significant Lower Costs

Among the most obvious reasons for why you would actually opt for any low code platform is that in reality, low code results in lower cost. Low code development leads to faster app development which saves a lot of time and as a result, lower cost.

It's not only good for companies but also for developers. It certainly cut out the intermediaries, and while they charge less, they use fewer resources and finally come out on top. It is fun for developers because it stops them from actually finding themselves stuck on one particular project which seems to last forever. This is why most of the companies hire app developer who is a well-versed with low-code development.

3. Better Accessibility

The lesser amount of code an application uses, the lesser bandwidth is needed to download it as well as run it. This is quite good news for the people who are based in rural areas or in different developing countries where access to the internet isn’t as prevalent as Western countries. Also, as low code applications can easily be created quite easily than a traditional app, they can easily be released much more swiftly and at a much lower price, and sometimes for free. iPhone app development services follow this approach because it will help in increasing the uptake of their apps as it reduces the entry barrier for every person from lower-income families.

Innovative Development Approach

Among the most promising instances of a low-code or no-code platform is Uber. The apps tap into Google for Maps, Dropbox for storage, Braintree for payments and much more. The most interesting thing about this is that app programming interfaces of APIs which Uber actually relies upon are easily available to anyone who wishes to use them. Uber took those APIs and then used them to create, which was new without requiring to develop each of those particular individual elements, all by themselves. They developed their own brand on top of it by means of looking at how they could actually differentiate themselves from the rest of the others. Mobile app development services should follow this example to create their own low code mobile app which disrupts the market.

The best thing about this is that it inspires innovation. At present, the marketplace actually decides, and only the best applications rise to the top. Also, low code development easily allows developers to iterate much more quickly and can aim for higher more.

The Role of Artificial Intelligence (AI)

Artificial Intelligence is certainly making big waves in different businesses, and as this technology improves further, it will find its way in different other uncharted areas. Among those areas is the low code app development, where it comes in quite useful for a wide range of tasks and actions including the integration of various data sources or just making sense of an entire unstructured or semi-structured data.

Artificial Intelligence is quite great at analysing and conducting trial and error. Hence, it won’t be quite long until the usage of AI becomes quite a standard part of the low code app development. A mobile application development company can find ways to reduce the total amount of code that it is using through AI and flagging potential and possible improvements.

Conclusion

It is quite certain that low-code or no-code app development is the future of app development for one of the simplest reasons that it is quite easier as well as faster and efficiently uses time. It actually doesn’t matter whether Android app development services or iPhone app development services are on-board with this particular change or not. This is quite inevitable as this approach is the path of least resistance. Also, as the inherent demand for low code platforms keeps in growing, developers will certainly find themselves to adopt it.

It is quite a great news as it will push the developers of mobile application development services to become the best. Also, there won’t be any time to redoing it to create the same thing, or any room for sloppy code as well as lengthy development processes which makes the mobile apps redundant even before they are actually finished. Hence, low-code or no-code development will certainly lead the future of mobile app development, and mobile app developers certainly have to get on the bandwagon, one way or the other.

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