Self‐Powered Wireless Temperature Monitor System Based on Triboelectric Nanogenerator with Machine Learning
Xin Cui, Yuankai Zhou, Ruhao Liu, Jiaheng Nie, Yaming Zhang, Yaming Zhang, Pengyu Yao, Yan Zhang, Yan Zhang
Abstract
Triboelectric nanogenerator (TENG) can power wireless, real‐time sensing system with hybrid electromagnetic or piezoelectric power, or directly drive commercial LED without battery. However, it is a great challenge to directly drive wireless real‐time sensing system due to low energy density based on environment energy. Here, a self‐powered smart wireless temperature monitoring system that uses machine learning to accurately measure the ambient temperature is developed. A position modulation‐based TENG‐driven transmitter enables wireless communication and real‐time temperature monitoring. This machine learning‐based wireless sensor can accurately monitor the ambient temperature, with a recognition accuracy of up to 96.2%. This sensor architecture could potentially be used in low‐cost distributed sensors for environmental monitoring.