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基于AI图像处理的疲劳驾驶监测系统设计

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鉴于近年来交通事故频增,特别是疲劳驾驶成为重大安全隐患,深入开发了一种基于人工智能图像处理技术的疲劳监测系统,旨在分析该系统在交通安全领域的应用价值及其效能.该系统旨在减少交通事故发生,提升安全意识,保护驾驶员身心健康,以及促进技术创新.系统设计包含实时面部与肢体行为分析、GPS精确定位、即时图像捕获、自动预警系统、应急联络功能与移动应用定位查询,全面提升了安全监控能力.技术方面,系统采用了PERCLOS算法与YOLOv3模型以提高监测准确性,期望推动监测技术更广泛的应用和智能交通体系的进步.
The design of fatigue driving monitoring system based on AI image processing
Given the frequent increase of traffic accidents in recent years,especially fatigue driving has become a major safety hazard,this study develops an in-depth fatigue monitoring system based on artificial intelligence image processing technology,aim-ing to analyze the value of the application of this system in the field of traffic safety and its effectiveness.The system aims to reduce traffic accidents,improve safety awareness,protect drivers'physical and mental health,as well as promote technological innova-tion.The system design includes real-time facial and body behavior analysis,GPS precise positioning,instant image capture,auto-matic warning system,emergency contact function and mobile application location query,which comprehensively improves the safety monitoring capability.In terms of technology,the system adopts the PERCLOS algorithm and the YOLOv3 model to improve monitoring accuracy,with the expectation of promoting the wider application of monitoring technology and the advancement of in-telligent transportation systems.

fatigue drivingAIimage recognitionPERCLOS algorithm

陈怡帆、肖波、韩涛、张志勇、马定权、吴永哲、程莹

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湖北师范大学电气工程与自动化学院,黄石 435002

疲劳驾驶 AI 图像识别 PERCLOS算法

2024

现代计算机
中大控股

现代计算机

影响因子:0.292
ISSN:1007-1423
年,卷(期):2024.30(22)