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Japanese Surveillance Technology AI Guardman Previewed

By Nitish Singh / June 26, 2018

Japan is making life extremely difficult for shoplifters with the new Al Guardman surveillance technology. The AI-based security camera setup was designed by Carnegie Mellon University that takes advantage of 2D scanning instead of 3D to identify shoplifters. Japanese telecom giant NTT East and Earth Eyes Corp are behind the construction of the cameras that take advantage of the technology. The camera continually detects poses of all bodies that are visible to the lens and tries to match the poses with suspicious behavior. As soon as the camera detects any suspicious activity, shopkeepers are notified by a connected app.

Earth Eyes Corp is testing a prototype version of the technology, and so far, results have been quite promising. The technology has been in development at the Carnegie Mellon University for years and was picked up by NTT and Earth Eyes Corp after realizing the potential Al Guardman has. It is estimated that shoplifting incidents can be reduced by up to 40% with the use of the surveillance cameras.

https://www.youtube.com/watch?v=amJfTgiy4KE

The camera not only includes the 2D tracking technology, but also new deep learning methods that make video analysis faster than ever. Other companies across the world are also trying to replicate the new technology with solutions that offer similar features and results. The technology can also be used in public to track criminal suspects.

NTT revealed that the camera would be available for sale at $2,150 at the end of July. Users will also need to pay $40 if they want cloud support every month. NTT expects around 10,000 stores to make use of Al Guardman within the next three years. With any independent analysis of the technology yet to be made, it is unknown how effective the technology really is in real life.

What do you think of the Al Guardman surveillance technology? Let us know in the comments below. Get instant updates on TechNadu’s Facebook page, or Twitter handle.



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