Bringing 20/20 Vision to the Edge with AI Inferencing

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There is demand today for edge vision solutions that bring AI capabilities to a wide range of products and services, such as hard-hat detection, people counting, and license plate recognition.

vision-system.com, Dec. 05, 2022 – 

There is demand today for edge vision solutions that bring AI capabilities to a wide range of products and services, yet many companies lack the expertise or data science know-how to develop and train models and then integrate them with existing AI accelerators. To solve this problem, many companies are turning to pre-trained models that they can easily integrate into their devices to make them smarter and given them better vision. These models have been trained to perform the most common object detection capabilities such as hard-hat detection, people counting, face mask detection, and license plate recognition. In fact, they have also been optimized to work with an inference accelerator, which is basically the chip that performs the inferencing function.

The ability to do inferencing in edge products can be transformational for both the company developing the device and the consumer benefitting from its use. Below are a few use cases:

Hard-hat detection for plant safety applications: AI detection can ensure that employees are wearing hard hats in dangerous locations and if no hat is detected, an alert can go off or the machinery can be shut down.

Counting customers in crowded environments: This example involves the ability to count customers in crowded settings. In the retail space, it can enable capabilities like as pose estimation, which uses computer vision technology to detect and analyze human posture. The data gained from this analysis could enable brick-and-mortar retailers to better understand human behavior and foot traffic in their stores, enabling them to set up the store in a way that maximizes their retail sales and customer satisfaction.

Edge servers in factories, hospitals, financial institutions, and other enterprises: For example, in the industrial space, AI can be used to help manage inventories, detect, or even predict defects before they happen.

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