tinyML Summit 2023:Personal Computing devices use-case and applications enabled by Smart Sensors

Personal Computing devices use-case and applications enabled by Smart Sensors
Nick THAMMA, Engineering Manager CMIT Sensor & Vision Architecture, HP
Mahesh CHOWDHARY, Fellow and Senior Director of MEMS Software Solutions , STMicroelectronics

Smart Sensors are enabling a distributed computing approach which significantly reduces the bandwidth requirement for transferring sensor data when the edge computing capabilities in MCUs or sensors are utilized. STMicroelectronics offers smart sensors, such as LSM6DSOX, which have a built-in Machine Learning Core (MLC) and Finite State Machine (FSM).

This capability allows the user to develop a variety of applications for consumer devices such as laptop, smartwatches or wireless sensor nodes where power consumption for applications needs to be minimized. These advanced sensors are increasingly being used to build solutions with an always-on user experience with extremely low current consumption, in order of single-digit micro-amps for sensor applications, such as activity tracking, gesture recognition, and vibration monitoring. A decision tree or a finite state machine can be downloaded into the sensor to build functionality such as human activity tracking.

By integrating ST’s latest IMU with an embedded ML core into our devices, our engineering team at HP worked with ST’s experts to build and train an AI model for recognizing various user activities based on device and user motion. Because of this work, our PC’s are now able to intelligently manage it’s thermals and power states for best comfort in using the PC off the desk and best battery life when on the go. A set of features enabled on personal computing devices will be presented by HP.

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