Machine learning algorithm for self-powered wireless humidity sensor system

Yuankai Zhou; Yan Zhang

doi:10.1117/12.3051629

18 November 2024 Machine learning algorithm for self-powered wireless humidity sensor system

Yuankai Zhou, Yan Zhang

Proceedings Volume 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) ; 134032S (2024) https://doi.org/10.1117/12.3051629
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, 2024, Zhengzhou, China

Abstract

Wireless self-powered sensors are necessary for long-term, large-scale, real-time environmental monitoring systems. Triboelectric nanogenerators can capture energy from the environment to power sensors. However, fewer works that directly transform energy into wireless sensing signals, and the majority of existing environmental sensors require energy storage devices to store energy. Direct-driven wireless self-powered sensing is further limited by low energy density in the environment. In this paper, we present a wireless humidity sensor system that is suitable for ambient energy harvesting. This method can be used in self-powered ambient energy harvesting devices to convert and modulate environmental energy into a sensing signal without any energy storage devices. The signal is processed by using a machine learning algorithm, and the humidity recognition accuracy can reach 98.7%.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuankai Zhou and Yan Zhang "Machine learning algorithm for self-powered wireless humidity sensor system", Proc. SPIE 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) , 134032S (18 November 2024); https://doi.org/10.1117/12.3051629

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