Battery-powered AI/ML-based smart alarm system
Infineon Technologies has introduced a battery-powered Smart Alarm System (SAS). The technology platform achieves high accuracy and very low-power operation using sensor fusion based on artificial intelligence/machine learning (AI/ML). This technology combined with low-power wake-on acoustic event detection provides remarkable performance. The compact design exceeds the detection accuracy of acoustic-only alarm systems used today in smart buildings and homes, and other IoT applications while achieving equal or greater battery life compared to less sophisticated solutions.
“We have enabled a unique and differentiated approach to bringing AI/ML capabilities to cost-sensitive, battery-powered home security sensor systems, without sacrificing battery life,” said Laurent Remont, Vice President of IoT and Sensor Solutions at Infineon’s Power and Sensor Systems Division. “Current home security systems are unreliable for detecting events such as glass break. Our new Smart Alarm System combines a number of best-in-class technologies to create an alarm system that is smart, reliable and power efficient.”
The Smart Alarm System incorporates Infineon’s high signal-to-noise ratio (SNR) analog XENSIV™ MEMS microphone IM73A135V01, XENSIV digital pressure sensor DPS310 and PSoC™ 62 microcontroller. Infineon also provides a sensor fusion software algorithm based on precisely trained AI/ML that combines acoustic and pressure sensor data to accurately differentiate between sharp sounds inside a home and distinctive audio/pressure events. These events can be created when glass is broken, or a house alarm is triggered due to a smoke alarm, a carbon monoxide alarm or an intrusion is detected through a door or window.
The AI/ML sensor fusion algorithm is also capable of eliminating many other background sounds or background pressure events that can generate false positives due to the similarities to alarm systems.
The home security alarm SAS reference design technology is available today, with the board available in September 2022.
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