Watch a 12-minute conference video presentation from tinyML Asia 2022 exploring an innovative contactless fitness tracking solution that uses radar technology and edge computing. Learn about the development of a privacy-preserving system that employs a Texas Instruments IWR1843 mmWave radar board and ESP32 module to detect and classify eight different exercises with 97% accuracy. Discover how this compact device creates Velocity-Time maps to identify unique movement signatures, processes data using a three-layered Convolutional Neural Network, and transmits results via Bluetooth Low Energy to smartphones. Understand the advantages of this radar-based approach over traditional wearable and camera-based fitness trackers, including enhanced user comfort and built-in privacy protection through point cloud data collection.
tinyRadar for Fitness: A Radar-Based Contactless Activity Tracker for Edge Computing
EDGE AI FOUNDATION via YouTube
Overview
Syllabus
tinyML Asia 2022 Video Poster: tinyRadar for fitness: A radar-based contactless activity tracker...
Taught by
EDGE AI FOUNDATION