• The SmartEdgeML solution allows users to build, test, tune, and deploy ML models at the sensor chip level
• SmartEdgeML includes: SmartMotion^TM ICM-45686-S 6-axis motion sensor, SmartBug 2.0 evaluation kit, and Sensor Inference Framework (SIF) software, now available for download
• SmartBug 2.0 (MD-45688-ML) will be available February 1 to evaluate SIF with ICM-45686-S

January 10, 2024

TDK Corporation (TSE:6762) announces the InvenSense SmartEdgeML^TM, an advanced edge ML solution enabling new possibilities for wearables, hearables, AR glasses, IoT, and other products that benefit from machine learning (ML) at the sensor chip level. SmartEdgeML is the first solution to generate and run machine learning models on a 2.5 x 3mm 6-axis motion sensor IMU at < 30 µA.

“TDK’s SmartEdgeML is a paradigm shift in edge machine learning, as it will allow developers, ODMs, and OEMs to implement ML-optimized motion sensor algorithms on an IMU sensor chip. This reduces the amount of raw data going to edge processors, which significantly improves device battery life, data privacy, and system latency,” said Sahil Choudhary, Director Motion Sensors and Software at InvenSense, a TDK Group company.

TDK also announces the availability of the InvenSense SmartBug 2.0 (MD-45686-ML), a multi-sensor wireless module consisting of the InvenSense ICM-45686-S IMU. This module works as the perfect evaluation system for users to get started with the InvenSense SIF and the ICM-45686-S IMU. The SIF is now available for download, while the MD-45686-ML and ICM-45686-S will be available at distributors by February 1, 2024.

There are three components of SmartEdgeML, which include:

• SIF (sensor inference framework): SIF, the software component of SmartEdgeML, is a complete machine learning framework by TDK, providing a one-stop-shop for users to collect IMU sensor data, select custom features, build ML models, test ML performance, deploy, and run those models on the ICM-45686-S IMU through the SmartBug 2.0. Tested examples include algorithms such as exercise classification (squats, jumping jacks, lateral raises, or push-ups) and wrist gesture classification (fight, turn, shake, or still).
• ICM-45686-S IMU: This is the hardware component of SmartEdgeML. The SmartMotion ICM-45686-S is a 2.5 x 3mm IMU from the TDK BalancedGyro^TM family that enables ML decision tree models to be run on-chip at the lowest current consumption (< 30 µA). This new IMU provides premium temperature stability and vibration rejection, making it optimal for applications such as AR glasses, VR, OIS, drones, TWS, and robotics that need a combination of high-performance and ultra-low power machine learning algorithms.
• SmartBug 2.0 (ML version): MD-45686-ML is an all-in-one multi-sensor wireless module that comes with the ICM-45686-S 6-axis motion sensor and is compatible with the SIF. The small form factor and BLE + USB interface of SmartBug 2.0 allows users to get started quickly with SIF so they can move easily from data collection to building ML models, to deploying on the ICM-45686-S IMU. This is the go-to device for getting started with SmartEdgeML. 

SmartEdgeML is being demonstrated at this week’s Consumer Electronics Show (CES) in Las Vegas from January 9-12, 2024. Come by the TDK booth #20521 in the CES Central Hall (LVCC) and look for the demo: “SmartEdgeML Machine Learning on a Chip” where you can build a machine learning algorithm on a 2.5*3 mm motion sensor in less than five minutes.

For more information about SmartEdgeML including the SmartBug 2.0, and to download the SIF software, visit invensense.tdk.com/smartedgeml or contact InvenSense Sales at sales.us@tdk.com.