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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.
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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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LUCA MARCHESE Aerospace_&_Defence_Machine_Learning_Company VAT:_IT0267070992 Email:_luca.marchese@synaptics.org |
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