A real-time fire and flame detection method for electric vehicle charging station based on machine vision

In the charging process of electric vehicle (EV), high voltage and high current charging methods are widely used to reduce charging time, resulting in severe battery heating and an increased risk of fire. To improve fire detection efficiency, this paper proposes a real-time fire and smoke detection...

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Veröffentlicht in:	Journal of real-time image processing Jg. 20; H. 2; S. 38
Hauptverfasser:	Gao, Dexin, Zhang, Shiyu, Ju, Yifan, Yang, Qing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2023 Springer Nature B.V
Schlagworte:	Accuracy Algorithms Cellular telephones Classification Clustering Computer Graphics Computer networks Computer Science Datasets Electric vehicle charging Electric vehicle charging stations Emergency procedures Fire detection Image Processing and Computer Vision Machine vision Monitoring Multimedia Information Systems Network management systems Neural networks Optimization Pattern Recognition Real time Signal,Image and Speech Processing Smoke Tracking Vision systems Kmeans + + clustering algorithm Fire smoke detection EV charging station CA module GhostNet-YOLOv4-CA
ISSN:	1861-8200, 1861-8219
Online-Zugang:	Volltext
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