Recognized as a finalist for a 2022 Best of Sensors Award at Sensors Converge, Aspinity has delivered its glass break detection sensor with a five-year battery life while eliminating false alarms to common household sounds.
Called the AML100 sensors, the always-listening solution is the first to implement sensing, processing and decision-making within the ultra-low-power analog domain, eliminating the digitization of irrelevant data and wasted power.
Aspinity sensors provide an array of security and home automation applications that require an extended battery lifetime including the detection of T3/T4 alarm tones.
“Consumers want home security systems that both run for years on battery and don’t trigger false alarms,” said Tom Doyle, founder and CEO at Aspinity. “Unfortunately, existing glass break sensors only deliver one or the other, which frustrates consumers and diminishes brand satisfaction. False alarms can also prove expensive if law enforcement charges a penalty when called to the scene for no reason.”
The company’s analog machine learning processor enables low-power, always-on machine learning architecture with algorithms that are trained to detect window glass break. The analog machine learning chip uses near-zero power to inference analog data. The system-level approach eliminates the power penalty of digitization digital processing and transmission of irrelevant data, reducing always-on system power.
Sensors Converge is taking place this week in San Jose, California.