Design and implementation of indoor smokers detection and alarm system based YOLOv5

Hedan Liu; Xiao Lin; Hanping Ye; Jian Wang

doi:10.1117/12.2653462

8 December 2022 Design and implementation of indoor smokers detection and alarm system based YOLOv5

Hedan Liu, Xiao Lin, Hanping Ye, Jian Wang

Proceedings Volume 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022); 1247418 (2022) https://doi.org/10.1117/12.2653462
Event: Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 2022, Guilin, China

Abstract

In order to solve the automatic detection and alarm of indoor smokers, this paper designs and implements an indoor smoker detection and alarm system based on YOLOv5 model. This paper uses YOLOv5 as the target recognition model to complete the recognition of cigarettes and human objects, uses Deepsort target tracking algorithm to achieve the determination of smoking action, and combines Facenet face recognition algorithm and sklearn framework and other technologies to achieve face recognition and alarm function. The test experiment proves that the accuracy rate of the smoking person detection and alarm system based on the method of this paper is high and has certain practical and promotion prospects.

Citation Download Citation

Hedan Liu, Xiao Lin, Hanping Ye, and Jian Wang "Design and implementation of indoor smokers detection and alarm system based YOLOv5", Proc. SPIE 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 1247418 (8 December 2022); https://doi.org/10.1117/12.2653462

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