Artificial intelligence (AI) plays an important role in the digital age. Self-learning algorithms have the ability to improve processes and use them in manufacturing, testing, and diagnosis. It's also because image solutions always work with a fixed system, doing a lot or changing quickly is a big challenge.

Artificial intelligence, on the other hand, can easily solve these problems. So where is the technical challenge? And how can we make it widely accepted? 

The challenges for the application of AI-based image processing are still high. This usually requires skill, effort, and investment in hardware and storage. Not only training a neural network, but also using it and evaluating its results requires knowledge of hardware, software and interfaces.

This creates a challenge for many businesses. IDS suggests it may be different. The IDS NXT AI vision system (www.ids-nxt.com) comes with all the necessary tools and functions, allowing users to easily create creative solutions.

The cloud-based IDS NXT Lighthouse software allows users with no prior experience in artificial intelligence or camera programming to train neural networks. As it is a web-based application, all necessary features and procedures are immediately available. Engineers or programmers don't need to set up their own development environment, but can start training their own neural networks right away.

It requires three simple steps. Download sample images, labels, start automatic training. Network design can run directly on the IDS NXT professional camera, which can transmit required data or send commands to connected machines via REST or OPC UA. Deep Learning: A Revolution in Automation

One thing is true. Artificial intelligence is changing the game. This technology has entered a new field such as the medical field of incredible complexity, making applications that make conventional images too expensive, inconvenient and difficult. Dr. Alexander Windberger, AI specialist at IDS Imaging Development GmbH, explains: "Not only has the game changed, but so has the player. AI-based imaging works differently than image processing which is legal , because the results are 100%. But most importantly the data is used. It is determined by the quality of the set.

Therefore, users will need various skills to use AI Vision. It changes the way work is seen and worked on. Recording experts emerge because they can continue to use their knowledge to create useful information and can easily react to changing information and ideas while doing so. However, many companies are still skeptical of the new technology. You don't have the skills and don't have the time to get to grips with the details.

 At the same time, the AI Vision community is growing in the IoT sector and in startups. New applications and new user groups inevitably have different uses and policies. Traditional SDKs are not enough to provide optimal support for all tasks, from generating and training data to working with neural networks.

Dr. Windberger had this to say about the future: This improves the usability of the device and reduces the impact on access, which now accelerates the speed of AI-based image processing. Ultimately, AI is a human tool and should be used intuitively and effectively. "

Driver of current development

No other product collects and interprets as much data as imagery. This allows you to monitor, process and report results to additional results in the network, such as object characteristics (such as measurement), status ("available / not available") or good. Artificial intelligence adds another layer to the picture and comes into play when making good decisions. This will open a brand new app.

Automation with smart cameras has the ability to more easily respond to complex business processes while being effective and efficient. Businesses that are far from moving to end-to-end digitization and automation can progress with AI-powered image processing. Holistic, user-friendly systems like IDS NXT pave the way for this.