北京市西城区城市公共设施状态监测图像数据集

本数据集专用于训练和优化针对北京市西城区城市公共设施状态的视觉识别模型，旨在智能、精准地识别辖区内公共设施(含相关配套设施)存在的五类典型问题：单车倒伏、井盖异常（非缺失的其他异常表现）、井盖异常（缺失）、座椅损坏、道路护栏损坏。
应用目标为服务于西城区的道路日常巡检、预防性养护与应急维修工作。通过将AI识别模型集成于智慧城管平台，实现对管辖范围内城市主干道、辅路、胡同街巷等区域的7x24小时自动化监测。具体流程为：系统自动发现问题 -> 平台生成工单并派发 -> 养护单位现场处置 -> 核查验收结案。该应用有效改变了依赖人工巡查的传统模式，大幅提升了公共设施状态的发现效率、处置速度和全区道路设施的精细化管理水平，为保障公共安全、提升城市形象提供关键技术支撑。

This dataset is specifically designed for training and optimizing visual recognition models for the status of urban public facilities in Xicheng District, Beijing. It is intended to intelligently and accurately identify five typical problems occurring in public facilities (including related supporting facilities) within its jurisdiction: fallen bicycles, abnormal manhole covers (other non-missing abnormalities), missing manhole covers, damaged seats, and damaged road guardrails. Its application purpose is to support daily road inspection, preventive maintenance and emergency repair work in Xicheng District. By integrating the AI recognition model into the smart urban management platform, 7x24-hour automated monitoring can be implemented for areas under its jurisdiction, including urban main roads, auxiliary roads, hutongs and street lanes. The specific workflow is as follows: the system automatically detects problems -> the platform generates and dispatches work orders -> the maintenance unit conducts on-site disposal -> verification and acceptance lead to case closure. This application effectively transforms the traditional manual inspection-based mode, greatly improving the efficiency of detecting public facility status, the speed of disposal, and the refined management level of road facilities across the entire district, providing critical technical support for ensuring public safety and enhancing the urban image.