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UNO™ is a safety camera with safe privacy. The camera works through the background subtraction mechanism. The background is learned at the time of installation. All people who enter the background are seen as shadows, and the machine learning model trains a series of positions that represent imminent danger, a fall, or another accident. The camera does not transmit images to the outside but only has a Boolean electrical interface that signals a dangerous situation. In fact, the camera was designed to comply with all regulations on people's privacy.

The UNO™ camera has been designed using the ZISC® (Zero Instruction Set Computer®) chip with 78 neurons by Silicon Recognition®. The chip that today has 1000/5000 neurons is called Neuromem® and is marketed by General Vision®.

UNO™ has been realized in 2002 as part of a research project funded by a large company in the security sector.

 

The camera was designed on a MUREN® (MUltimedia Recognition ENgine) board from Silicon Recognition with two ZISC78 chips and a plug-in CMOS camera. The design required reconfiguring the FPGA with new VHDL code.

 

 

 

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