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Research on the Optimization of Spatial Layout of Video Surveillance in Urban Residential Areas Based on Crime Prevention
王益 江安邦 李早 刘国元 张拾斤 杨璐 翁欣然‖Wang Yi, Jiang Anbang, Li Zao, Liu Guoyuan, Zhang Shijing, Yang Lu, and Weng Xinran
当前住区视频监控设施的空间布局主要依靠相关人员的主观经验进行布设，未考虑住区空间结构特征和犯罪分布特点，易造成监控质量较低、监控资源浪费等问题。为提高视频监控设施的监控质量，实现监控资源的合理分配，本文提出了一种面向犯罪预防的住区视频监控设施的空间布局优化方法。首先基于网格化的思想对住区区域进行区域划分，从住区犯罪预防角度建立了住区期望监控资源分配矩阵以描述各区域对监控资源的需求情况。然后，建立视频监控设施监控资源贡献矩阵描述视频监控设施的监控范围。同时依据住区的空间结构选取监控设施候选点，以避免建筑物对视频监控设施的遮挡。据此建立以期望监控资源分配矩阵与实际监控资源分配矩阵平均差异最小为目标，考虑视频监控设施选型选址和建设成本约束的住区视频监控设施空间布局优化模型，并利用遗传算法求解该优化模型。最后通过仿真算例验证了该模型在提高住区监控质量，实现监控资源合理分配的适用性和有效性。
The current spatial layout of video surveillance in urban residential areas primarily relies on the subjective assessments of personnel, which often results in issues like inadequate surveillance quality and inefficient resource use. To enhance monitoring effectiveness and ensure the rational allocation of surveillance resources, this paper proposes an optimization method for the spatial layout of residential video surveillance aimed at crime prevention. First, the residential area is divided into grids. From a crime prevention perspective, we construct an expected resource allocation matrix that outlines the demand for surveillance in each grid section. Next, we develop a surveillance resource contribution matrix to illustrate the coverage provided by the video surveillance systems. Additionally, candidate locations for surveillance cameras are identified based on the spatial structure of the residential area, ensuring that buildings do not obstruct the view. Using these components, we establish a spatial layout optimization model for residential video surveillance, which is then solved using a genetic algorithm. Finally, we present a simulation example to demonstrate the model's applicability and effectiveness in enhancing the quality of residential video surveillance networks while optimizing resource allocation.
城市住区；视频监控设施；空间布局优化；犯罪预防
urban residential areas; video surveillance; spatial layout optimization; crime prevention
图3 单个监控设施形成的监控资源贡献矩阵
图4 多个监控共同形成的监控资源贡献矩阵
图6 犯罪的核密度分析和住宅区的视角整合度分析
图9 住宅视频监控优化前后的布局图
王益，合肥工业大学建筑与艺术学院副教授、研究生导师。
Wang Yi, Associate Professor, Supervisor of Postgraduate Student, College of Architecture and Art, Hefei University of Technology, Heifei, P. R. China.
江安邦（通讯作者），合肥工业大学土木与工程学院研究生。
Jiang Anbang (corresponding author), Postgraduate Student, College of Civil Engineering, Hefei University of Technology, Heifei, P. R. China. Email: 2020170648@mail.hfut.edu.cn
李早，安徽建筑大学建筑与规划学院副校长、教授、博士生导师。
Li Zao, Vice President, Professor, Supervisor of PhD Candidate, School of Architecture and Planning, Anhui Jianzhu University, Heifei, P. R. China.
刘国元 ，中铁合肥建筑市政工程设计研究院有限公司副总经理、院总建筑师、国家一级注册建筑师、正高级工程师。
Liu Guoyuan, Vice President, Chief Architect, National First-Level Registered Architect, Senior Engineer, China Railway Hefei Institute of Architectural and Municipal Engineering Design Co., Ltd. Heifei, P. R. China.
张拾斤，合肥工业大学土木与工程学院研究生。
Zhang Shijing, Postgraduate Student, College of Civil Engineering, Hefei University of Technology, Heifei, P. R. China.
杨璐，合肥工业大学土木与工程学院研究生。
Yang Lu, Postgraduate Student, College of Civil Engineering, Hefei University of Technology, Heifei, P. R. China.
翁欣然，合肥工业大学建筑与艺术学院实验师。
Weng Xinran, Test Engineer, College of Architecture and Art, Hefei University of Technology, Heifei, P. R. China.
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