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

Lulu Hou¹, Wenrui Duan¹, Guozhe Xuan^2,3,4,5,6

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

Sensors (Basel, Switzerland)

|April 13, 2023

Summary

This study introduces a small, low-power intelligent microsystem for wireless acoustic sensor networks (WASNs) in the Internet of Things (IoT). It accurately recognizes sound events, enabling smart applications in homes and security.

Keywords:

BLE mesh acoustic signal processing edge computing intelligent microsystem meshed network sound event recognition wireless acoustic sensor network

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Area of Science:

Intelligent microsystems
Wireless acoustic sensor networks (WASNs)
Internet of Things (IoT)

Background:

Microsystems are vital for autonomous edge computing in IoT.
Low-power, small, and lightweight designs are essential for networked cooperative work.
Existing solutions may lack integrated sound sensing and recognition capabilities.

Purpose of the Study:

To present an innovative intelligent microsystem for WASNs.
To enable autonomous sound sensing and event recognition at the edge.
To develop a compact, low-power solution for IoT applications.

Main Methods:

Designed a microsystem with optimized sensing, energy, processing, and transceiver modules.
Integrated a low-computational Convolutional Neural Network for sound event recognition.
Formed a meshed WASN using low-power Bluetooth Mesh networking.

Main Results:

Achieved a microsystem size of 7.36 cm³ and weight of 8 g.
Demonstrated sound event recognition accuracy over 92.50% for alarm and water flow sounds.
Enabled wireless communication within a 5 m range.

Conclusions:

The developed microsystem is suitable for home IoT and border security applications.
The meshed WASN offers easy accessibility, scalability, and smartphone manageability.
The system provides an effective solution for low-power, intelligent sound monitoring in IoT.