Smart Touchless Control with Credit-Card Sized Radar Sensor and Microcomputer
Philip Hann Yung Lee, Yilong Lu · 2022 IEEE 11th Global Conference on Consumer Electronics (GCCE) · 2022
A smart, low-cost, stand-alone, and reliable touchless human-computer interaction (HCI) using a tiny 60 GHz radar sensor and a small Raspberry Pi microcomputer with advanced radar signal processing and machine learning (ML), is proposed and implemented. Three feature extraction techniques and various ML algorithms are explored and compared. Smart gesture classification is realized by an ensemble ML model with 3 non-deep and deep learning (DL) algorithms and the majority voting scheme to improve classification accuracy. Both radar signal processing and ML algorithms are implemented in Python language in a Raspberry Pi microcomputer with an optimization by TensorFlow Lite, which reduces DL CPU time by 120 times. The proposed HCI is also integrated with a menu driven use case, which could be easily adapted to many other gesture control applications for home and industrial appliances.