基于YOLOv5的抽烟检测系统设计
Design of Smoking Detection System Based on YOLOv5
刘飞燕 1唐瑶 1赵正伟1
作者信息
- 1. 广西民族大学 数学与物理学院,广西 南宁 530006
- 折叠
摘要
针对公共禁烟场所中自动检测识别抽烟行为的问题,提出了基于YOLOv5目标识别算法的抽烟检测系统.该系统主要有目标识别模块、语音播报模块、摄像头模块和数据库模块,实验使用Python语言在PyCharm开发平台上对目标识别功能和数据库模块进行设计和编程实现,通过Arduino开发平台连接SYN6288 语音播报模块,实现抽烟行为的智能检测识别,对抽烟检测研究有一定的参考意义.
Abstract
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.
关键词
YOLOv5/抽烟检测/目标识别/语音播报Key words
YOLOv5/smoking detection/target recognition/voice broadcast引用本文复制引用
基金项目
广西民族大学国家级大学生创新创业训练计划(202210608127)
广西民族大学国家级大学生创新创业训练计划(202210608126)
出版年
2024
国家科技期刊平台
NSTL
万方数据