Recently, the research group of Prof. Haiwu Zheng from the School of Physics and Electronics has made new progress in the field of intelligent sound monitoring and identification by triboelectric nanogenerator. The paper entitled “Intelligent sound monitoring and identification system combining triboelectric nanogenerator-based self-powered sensor with deep learning technique” was published in Advanced Functional Materials (https://doi.org/10.1002/adfm.202112155). The postgraduate Hongbo Yao is the first author, lecturer Jiawei Zhang, Prof. Haiwu Zheng and Prof. Dayan Ban are the corresponding authors.

Figure 1. Schematic diagram of the application scenario of Wireless Acoustic Sensor Networks based on SDTENG.

Urban sound management is required in a variety of fields such as transportation, security, water conservancy and construction, among others. Given the diverse array of available noise sensors and the widespread opportunity to connect these sensors via mobile broadband Internet access, many researchers are eager to apply sound-sensor networks for urban sound management. Existing sensing networks typically consist of expensive information-sensing devices, the cost and maintenance of which limit their large-scale, ubiquitous deployment, thus narrowing their functional measurement range. Herein, an innovative, low-cost, sound-driven triboelectric nanogenerator (SDTENG)-based self-powered sensor is proposed, from which the SDTENG is primarily comprised of fluorinated ethylene propylene membranes, conductive fabrics, acrylic shells, and Kapton spacers. The SDTENG-based sensor was integrated with deep learning technique in the present study to construct an intelligent sound monitoring and identification system, which is capable of recognizing a suite of common road and traffic sounds with high classification accuracies of 99 % in most cases. The novel SDTENG-based self-powered sensor combined with deep learning technique has demonstrated a tremendous application potential in urban sound management, which will show the excellent application prospects in the field of Ubiquitous Sensor Networks.

This work was supported by the National Natural Science Foundation of China (Nos.52072111 and 51872074), Natural Science Foundation of Henan Province in China (212300410004), and the Scientific and Technological Project in Henan Province of China (212102210025 and 212102210274). D.B. acknowledged the financial support from the Natural Science and Engineering Research Council (NSERC) of Canada and Ontario Centre of Innovation (OCI).

Advanced Functional Materials is an international famous journal owned by Wiley-VCH Verlag. The latest published impact factor of the journal is 18.808.

The link to the paper is https://onlinelibrary.wiley.com/doi/abs/10.1002/adfm.202112155.

From: School of Physics and Electronics