02.12.19
STMicroelectronics has integrated machine-learning technology into its advanced inertial sensors to improve activity-tracking performance and battery life in mobiles and wearables.
The LSM6DSOX iNEMO sensor contains a machine-learning core to classify motion data based on known patterns. Relieving this first stage of activity tracking from the main processor saves energy and accelerates motion-based apps such as fitness logging, wellness monitoring, personal navigation and fall detection.
“Machine learning is already used for fast and efficient pattern recognition in social media, financial modeling, or autonomous driving,” said Andrea Onetti, Analog, MEMS and Sensors Group VP, STMicroelectronics. “The LSM6DSOX motion sensor integrates machine-learning capabilities to enhance activity tracking in smartphones and wearables.”
The LSM6DSOX iNEMO sensor contains a machine-learning core to classify motion data based on known patterns. Relieving this first stage of activity tracking from the main processor saves energy and accelerates motion-based apps such as fitness logging, wellness monitoring, personal navigation and fall detection.
“Machine learning is already used for fast and efficient pattern recognition in social media, financial modeling, or autonomous driving,” said Andrea Onetti, Analog, MEMS and Sensors Group VP, STMicroelectronics. “The LSM6DSOX motion sensor integrates machine-learning capabilities to enhance activity tracking in smartphones and wearables.”