Electric bikes charging anomaly detection from alternating current side based on big data

Yang, Fang; Yang, Yang; Wang, Xu; Ouyang, Xin; Shuai, Chunyan

doi:10.1016/j.engappai.2024.109042

Engineering Applications of Artificial Intelligence

2024

DOI: 10.1016/j.engappai.2024.109042

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Electric bikes charging anomaly detection from alternating current side based on big data

Fang Yang,

Yang Yang,

Xu Wang

et al.

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2024

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Edge Artificial Intelligence for Electrical Anomaly Detection Based on Process-In-Memory Chip

Jin,

Qiu,

2024

Electronics

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Neural-networks (NNs) for the current feature analysis bring novel electrical safety functions in smart circuit breakers (CBs), especially for preventing the fire hazard from electric vehicle/bike battery charging. In this work, the edge artificial intelligence (AI) solutions for the electrical anomaly detection were designed and demonstrated based on the process-in-memory (PIM) AI chip. The ultra-low power and high-performance character of PIM AI chips enable the edge solution to embed in the limited space inside the circuit breaker and to detect improper battery charging at millisecond latency.

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Edge Artificial Intelligence for Electrical Anomaly Detection Based on Process-In-Memory Chip

Jin,

Qiu,

2024

Electronics

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show abstract

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Electric bikes charging anomaly detection from alternating current side based on big data

Cited by 1 publication

References 33 publications

Edge Artificial Intelligence for Electrical Anomaly Detection Based on Process-In-Memory Chip

Edge Artificial Intelligence for Electrical Anomaly Detection Based on Process-In-Memory Chip

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