Intelligent Microsystem for Sound Event Recognition in Edge Computing Using End-to-End Mesh Networking

Author:

Hou Lulu1,Duan Wenrui1,Xuan Guozhe23456,Xiao Shanpeng78,Li Yuan78,Li Yizheng78,Zhao Jiahao23456

Affiliation:

1. School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing 100192, China

2. Department of Precision Instrument, Tsinghua University, Beijing 100084, China

3. Key Laboratory of Smart Microsystem (Tsinghua University), Ministry of Education, Beijing 100084, China

4. State Key Laboratory of Precision Measurement Technology and Instruments, Beijing 100084, China

5. Beijing Laboratory of Biomedical Detection Technology and Instrument, Beijing 100084, China

6. Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100084, China

7. China Mobile Research Institute, Beijing 100053, China

8. The IoT Intelligent Microsystem Center, Tsinghua University-China Mobile Joint Research Institute, Beijing 100084, China

Abstract

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 cm3 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.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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