Artificial intelligence (AI) applications in automation already cover a broad spectrum, although the technology is early. From autonomous mobile robots and the dramatic improvement of quality control through logic control, food safety and predictive maintenance, it is apparent that AI will play a key role in automation in the foreseeable future.
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How does it work?
Consider Ai vision cameras as a puzzle jigsaw. You have to assemble several pieces to create an image. That’s precisely how computer vision neural networks work. The neural networks differentiate between different image parts and identify the sub-component model.
Rather than giving suggestions for recognising an object, the computer is fed with images that can help to identify an object accurately. Suppose you have a computer to train to identify a cat. Instead of giving clues like various tails, whiskers, sharp ears, the system is supplied with hundreds (or millions) of cat images.
- Ai vision cameras offers the great advantage of being an integrated complete AI solution adapted quickly and effortlessly to the task at hand. Users do not have to deal with the acquisition of images, I/O handling, or other essential functions. Still, they can focus on the development from the start of the actual image processing solution.
- Usually, implementing applications in one working day is no problem for Linux, AI, and image processing developers. This is the integrated software from Vision AI, which offers the user a large number of sample applications. A quick adaptation to the specifications can be made on this basis. Vision AI is especially predestinated to create solutions that require technologies like AI, Deep Learning or Machine Learning, thanks to the Google Edge TPU.
- In addition to adapting the sample applications offered, AI solutions for businessesalso have the flexibility to develop their own Halcon, C++ or Python image processing applications and integrate their library or software developments. Free programming from VisionAI makes selecting suitable software extremely flexible and allows full access to the hardware, allowing users to control the design of their integrated VisionAI solution fully.
- At Vision AI, a Cortex-A53 Quad Core ARM processor supports the TensorFlow Lite and the Auto ML Vision Edge, featuring a modern Debian-based Linux operating system and a clock speed of 4×1.8 GHz. With a resolution of 5 megapixels, the global CMOS shutter sensor achieves a frame rate of 65 full frames per second. Two digital inputs and four digital outputs, and an Ethernet interface with 1000 Mbit/s are available for communication with the connected machine or process. Combined with a minimal design of just 50 mm to 50 mm per 40.1 mm, full booth, and the possibility of connecting C-mount lenses into an optional protecting booth, Vision AI is a perfect built-in vision solution for applications in AI solutions for businesses.
- Food & Drink
Many foodstuffs are not visually identical but subject to natural variations when manufactured.
If people’s health is dependent on the reliability of an image processing system, safe solutions are needed.
They require robust vision systems that can resist these conditions about temperatures, dirt, and ambient light.