Adaptive decentralized AI scheme for signal recognition of distributed sensor systems

Shixiong Zhang; Hao Li; Cunzheng Fan; Zhichao Zeng; Chao Xiong; Jie Wu; Zhijun Yan; Deming Liu; Qizhen Sun

doi:10.29026/oea.2024.240119

Opto-Electronic Advances (Dec 2024)

Adaptive decentralized AI scheme for signal recognition of distributed sensor systems

Shixiong Zhang,
Hao Li,
Cunzheng Fan,
Zhichao Zeng,
Chao Xiong,
Jie Wu,
Zhijun Yan,
Deming Liu,
Qizhen Sun

Affiliations

Shixiong Zhang: School of Optical and Electronic Information, National Engineering Research Center of Next Generation Internet Access-system, Huazhong University of Science and Technology, Wuhan 430074, China
Hao Li: School of Optical and Electronic Information, National Engineering Research Center of Next Generation Internet Access-system, Huazhong University of Science and Technology, Wuhan 430074, China
Cunzheng Fan: School of Optical and Electronic Information, National Engineering Research Center of Next Generation Internet Access-system, Huazhong University of Science and Technology, Wuhan 430074, China
Zhichao Zeng: School of Optical and Electronic Information, National Engineering Research Center of Next Generation Internet Access-system, Huazhong University of Science and Technology, Wuhan 430074, China
Chao Xiong: Nanjing Research Institute of Electronic Equipment, Nanjing 210007, China
Jie Wu: Wenzhou Quality and Technology Testing Research Institute, Wenzhou 325000, China
Zhijun Yan: School of Optical and Electronic Information, National Engineering Research Center of Next Generation Internet Access-system, Huazhong University of Science and Technology, Wuhan 430074, China
Deming Liu: School of Optical and Electronic Information, National Engineering Research Center of Next Generation Internet Access-system, Huazhong University of Science and Technology, Wuhan 430074, China
Qizhen Sun: School of Optical and Electronic Information, National Engineering Research Center of Next Generation Internet Access-system, Huazhong University of Science and Technology, Wuhan 430074, China

DOI: https://doi.org/10.29026/oea.2024.240119
Journal volume & issue: Vol. 7, no. 12
pp. 1 – 13

Abstract

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Artificial intelligence (AI) plays a critical role in signal recognition of distributed sensor systems (DSS), boosting its applications in multiple monitoring fields. Due to the domain differences between massive sensors in signal acquisition conditions, such as manufacturing process, deployment, and environments, current AI schemes for signal recognition of DSS frequently encounter poor generalization performance. In this paper, an adaptive decentralized artificial intelligence (ADAI) method for signal recognition of DSS is proposed, to improve the entire generalization performance. By fine-tuning pre-trained model with the unlabeled data in each domain, the ADAI scheme can train a series of adaptive AI models for all target domains, significantly reducing the false alarm rate (FAR) and missing alarm rate (MAR) induced by domain differences. The field tests about intrusion signal recognition with distributed optical fiber sensors system demonstrate the efficacy of the ADAI scheme, showcasing a FAR of merely 4.3% and 0%, along with a MAR of only 1.4% and 2.7% within two specific target domains. The ADAI scheme is expected to offer a practical paradigm for signal recognition of DSS in multiple application fields.

Published in Opto-Electronic Advances

ISSN: 2096-4579 (Print)
Publisher: Institue of Optics and Electronics, Chinese Academy of Sciences
Country of publisher: China
LCC subjects: Science: Physics: Optics. Light
Website: http://www.oejournal.org/oea

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