Paper
28 April 2023 Research on distributed sensor network faulty recovery method based on attention mechanism
Zheng Xing, Boya Liu, Haochen Guan, Yiran Zhang, Ying Zhang
Author Affiliations +
Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126105I (2023) https://doi.org/10.1117/12.2671397
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China
Abstract
Faulty recognition and recovery are extremely essential components for existing sensor networks. However, current investigations concentrate on the recognition process and develop abundant advanced identification methods and existing recovery method is almost based on the multiple layers of neural network to achieve the recovery of sensor network, which would result in vast computation costs. Attention mechanism is proposed for neural network to focus some important neural nodes and perform high accuracy for training process with insignificant computation cost. In this article, we propose a novel neural network to recover the fault sensor network with attention mechanism. Thus, the developed mechanism can achieve rapid recovery of fault sensors network with reasonable computation costs and acceptable performance. From extensive experimental result, we can conclude that our proposed method can strictly process the fault sensor network and compared with existing fault sensor network recovery methods to illustrate the effective performance on recovery accuracy with reasonable costs of our proposed method.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zheng Xing, Boya Liu, Haochen Guan, Yiran Zhang, and Ying Zhang "Research on distributed sensor network faulty recovery method based on attention mechanism", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126105I (28 April 2023); https://doi.org/10.1117/12.2671397
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KEYWORDS
Sensor networks

Neural networks

Sensors

Education and training

Convolution

Data modeling

Data processing

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