文献类型：期刊文献

英文题名：Portable Intelligent Multi-Channel Electrochemical Analytical System with Self-Reconstruction Strategy and Edge Computing

作者：Li, Zhuoheng[1,2]; Sun, Hongyi[3]; Wang, Tao[4]; Ni, Wangze[1,2]; Zhu, Jiaqing[5]; Cheng, Weiwei[5]; Zhang, Bowei[4]; Xuan, Fuzhen[4]; Yang, Jianhua[1,2]; Zeng, Min[1]; Hu, Nantao[1,2]; Yang, Zhi[1]

机构：[1] Shanghai Jiao Tong University, National Key Laboratory of Advanced Micro and Nano Manufacture Technology, Shanghai, 200240, China; [2] School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Department of Micro/Nano Electronics, Shanghai, 200240, China; [3] School of Chemistry and Molecular Engineering, East China Normal University, Shanghai Key Laboratory for Urban Ecological Processes and Eco-Restoration, Shanghai, 200241, China; [4] School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai Key Laboratory of Intelligent Sensing and Detection Technology, Shanghai, 200237, China; [5] School of Materials Science and Engineering, Shanghai University of Engineering Science, Shanghai, 201620, China

年份：2024

外文期刊名：Proceedings of IEEE Sensors

收录：EI(收录号：20250317719370)

语种：英文

外文关键词：Anomaly detection - Electrochemical sensors - Network security - Solar power generation

摘要：Electrochemical sensors are of critical importance in a number of domains, including environmental monitoring, energy conversion, and biosensing. There is a clear trend toward miniaturization, intelligence, and wearability. Nevertheless, the versatility of these devices is frequently constrained by their bulkiness and cumbersomeness. In response to this challenge, this study developed a portable and intelligent multi-channel electrochemical analytical system equipped with chronoamperometry and cyclic voltammetry capabilities. A supplementary PCB adapter board connected by an FPC cable enables the support of up to eight independent channels. A software application has also been developed to enable real-time curve plotting, state control, and parameter adjustment. Additionally, the system employs self-reconstruction technology for automatic wide-range current measurement and incorporates edge computing for onboard anomaly detection. The proposed measurement system and data processing method highlight its extensive application prospects in the development of reliable and intelligent electrochemical devices. ? 2024 IEEE.