Aspinity has launched a dashcam evaluation kit and a suite of smart analogML algorithms for parked vehicle monitoring. The hardware/software offerings leverage the company’s always-on AML100 analog machine learning processor. The near-zero power AML100 enables continuous monitoring for extended periods without impacting the vehicle’s battery or requiring an external power source.
The company recently demonstrated a dashcam with a single microphone and an AML100 processor. The setup uses an acoustic-only trigger and analogML algorithms trained to identify automotive security events. According to Aspinity, the solution detects events more accurately than dashcams outfitted with a standard G-sensor. Surveillance algorithms detect such events as jiggling of the door handle, a neighboring car door opening into the vehicle, runaway shopping cart hitting the side of the car, and window glass breaking, while ignoring sounds from events unrelated to the vehicle.
Based on the AML100-REF-1 wireless, battery-operated reference module, the dashcam evaluation kit enables deployment and evaluation in the cabin of a vehicle. It consumes <50 µA in always-on mode and eliminates the video recording of false events that waste power.
To learn more about Aspinity’s AML100 monitoring solutions for automotive security, click here.
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