面向YOLO算法的城市监控布点优化设计

Optimization Design of Urban Monitoring Points Based on YOLO Algorithm

为了推动城市人机融合治理智慧化发展,本文研究并设计了基于YOLO算法的城市监控布点协同优化方案,从关键地点重点化、监控区域网格化、资源协同智慧化三个方面,优化传统监控布点模式和提高视频监控系统建设质量。实验结果表明,与传统监控布点模式相比,本文所设计的方案在检测识别车辆违停、垃圾乱扔等问题方面更加准确和全面,能够更加有效地加强社会治安防控体系建设。

In order to promote the intelligent development of urban human-machine integration governance,this article studies and designs a collaborative optimization plan for urban monitoring deployment based on YOLO algorithm.It optimizes the traditional monitoring deployment mode and improves the quality of video monitoring system construction from three aspects:focusing on key locations,grid monitoring areas,and intelligent resource collaboration.The experimental results show that compared to the traditional monitoring and distribution mode,the scheme designed in this article is more accurate and comprehensive in detecting and identifying issues such as vehicle violations and littering,and can more effectively strengthen the construction of social security prevention and control systems.