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Intelligent Microsystem for Sound Event Recognition in Edge Computing Using End-to-End Mesh Networking
Wireless acoustic sensor networks (WASNs) and intelligent microsystems are crucial components of the Internet of Things (IoT) ecosystem. In various IoT applications, small, lightweight, and low-power microsystems are essential to enable autonomous edge computing and networked cooperative work. This...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099044/ https://www.ncbi.nlm.nih.gov/pubmed/37050691 http://dx.doi.org/10.3390/s23073630 |
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author | Hou, Lulu Duan, Wenrui Xuan, Guozhe Xiao, Shanpeng Li, Yuan Li, Yizheng Zhao, Jiahao |
author_facet | Hou, Lulu Duan, Wenrui Xuan, Guozhe Xiao, Shanpeng Li, Yuan Li, Yizheng Zhao, Jiahao |
author_sort | Hou, Lulu |
collection | PubMed |
description | Wireless acoustic sensor networks (WASNs) and intelligent microsystems are crucial components of the Internet of Things (IoT) ecosystem. In various IoT applications, small, lightweight, and low-power microsystems are essential to enable autonomous edge computing and networked cooperative work. This study presents an innovative intelligent microsystem with wireless networking capabilities, sound sensing, and sound event recognition. The microsystem is designed with optimized sensing, energy supply, processing, and transceiver modules to achieve small size and low power consumption. Additionally, a low-computational sound event recognition algorithm based on a Convolutional Neural Network has been designed and integrated into the microsystem. Multiple microsystems are connected using low-power Bluetooth Mesh wireless networking technology to form a meshed WASN, which is easily accessible, flexible to expand, and straightforward to manage with smartphones. The microsystem is 7.36 cm(3) in size and weighs 8 g without housing. The microsystem can accurately recognize sound events in both trained and untrained data tests, achieving an average accuracy of over 92.50% for alarm sounds above 70 dB and water flow sounds above 55 dB. The microsystems can communicate wirelessly with a direct range of 5 m. It can be applied in the field of home IoT and border security. |
format | Online Article Text |
id | pubmed-10099044 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100990442023-04-14 Intelligent Microsystem for Sound Event Recognition in Edge Computing Using End-to-End Mesh Networking Hou, Lulu Duan, Wenrui Xuan, Guozhe Xiao, Shanpeng Li, Yuan Li, Yizheng Zhao, Jiahao Sensors (Basel) Article Wireless acoustic sensor networks (WASNs) and intelligent microsystems are crucial components of the Internet of Things (IoT) ecosystem. In various IoT applications, small, lightweight, and low-power microsystems are essential to enable autonomous edge computing and networked cooperative work. This study presents an innovative intelligent microsystem with wireless networking capabilities, sound sensing, and sound event recognition. The microsystem is designed with optimized sensing, energy supply, processing, and transceiver modules to achieve small size and low power consumption. Additionally, a low-computational sound event recognition algorithm based on a Convolutional Neural Network has been designed and integrated into the microsystem. Multiple microsystems are connected using low-power Bluetooth Mesh wireless networking technology to form a meshed WASN, which is easily accessible, flexible to expand, and straightforward to manage with smartphones. The microsystem is 7.36 cm(3) in size and weighs 8 g without housing. The microsystem can accurately recognize sound events in both trained and untrained data tests, achieving an average accuracy of over 92.50% for alarm sounds above 70 dB and water flow sounds above 55 dB. The microsystems can communicate wirelessly with a direct range of 5 m. It can be applied in the field of home IoT and border security. MDPI 2023-03-31 /pmc/articles/PMC10099044/ /pubmed/37050691 http://dx.doi.org/10.3390/s23073630 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hou, Lulu Duan, Wenrui Xuan, Guozhe Xiao, Shanpeng Li, Yuan Li, Yizheng Zhao, Jiahao Intelligent Microsystem for Sound Event Recognition in Edge Computing Using End-to-End Mesh Networking |
title | Intelligent Microsystem for Sound Event Recognition in Edge Computing Using End-to-End Mesh Networking |
title_full | Intelligent Microsystem for Sound Event Recognition in Edge Computing Using End-to-End Mesh Networking |
title_fullStr | Intelligent Microsystem for Sound Event Recognition in Edge Computing Using End-to-End Mesh Networking |
title_full_unstemmed | Intelligent Microsystem for Sound Event Recognition in Edge Computing Using End-to-End Mesh Networking |
title_short | Intelligent Microsystem for Sound Event Recognition in Edge Computing Using End-to-End Mesh Networking |
title_sort | intelligent microsystem for sound event recognition in edge computing using end-to-end mesh networking |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099044/ https://www.ncbi.nlm.nih.gov/pubmed/37050691 http://dx.doi.org/10.3390/s23073630 |
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