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基于YOLOV8框架的人员聚集和车辆拥堵检测

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智慧园区的出入口、办公大楼进出口等重要部位,会出现车辆拥堵和人员聚集的情况.目前数字视频监控设备无法做到智能化识别和报警,只能靠值班人员和巡逻人员进行人工监控、判断,无法有效、快速处理紧急和突发事件.本文选用YOLOv8目标识别框架技术,采用预训练模型和实际业务结合的工程实践方式,实现监控范围内的车辆和人员的数目识别.平台可以设置报警阈值以实现监控报警、系统联动和警报推送,处理突发和紧急事件,保证园区和办公楼的正常秩序.
People Gathering and Vehicle Congestion Detection Based on YOLOV8 Framework
Vehicle congestion and people gathering occur at the entrances and exits of smart parks,office buildings,and other important parts.At present,digital video surveillance equipment cannot achieve intelligent identification and alarm,which only rely on the personnel on duty and patrol personnel for manual monitoring and judgment,and cannot effectively and quickly deal with emergency accidents.In this paper,the YOLOv8 target recognition framework technology is selected,and the engineering practice method combining the pre-trained model and the actual business is used to identify the number of vehicles and personnel within the monitoring range.The platform can set alarm thresholds to achieve monitoring alarms,system linkage and alarm push,deal with emergency accidents,and ensure the normal order of parks and office buildings.

smart parkvehicle congestionpeople gatheringpre-trained modelsYOLOv8object detection

梁毅娟、孙伟、翟剑锟

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广西电力职业技术学院 广西 南宁 530007

北京中关村智酷双创人才服务股份有限公司 北京 100089

智慧园区 车辆拥堵 人员聚集 预训练模型 YOLOv8 目标检测

2023年度广西高校中青年教师科研基础能力提升项目

2023KY1370

2024

科学与信息化

科学与信息化

ISSN:
年,卷(期):2024.(13)