Design of Smoking Detection System Based on YOLOv5
A smoking detection system based on the YOLOv5 object recognition algorithm is proposed to address the issue of automatic detection and recognition of smoking behavior in public non-smoking places.The system mainly consists of a target recognition module,a voice broadcast module,a camera module,and a database module.The experiment uses Python language to design and program the target recognition function and database module on the PyCharm development platform,and connects to the SYN6288 voice broadcast module through Arduino development platform,so as to achieve intelligent detection and recognition of smoking behavior,which has certain reference significance for smoking detection research.
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