Urban underground pipelines have complex structures, long service lives, and are susceptible to illegal interference, corrosion, and external force damage. Therefore, they are a constant security risk that seriously threaten the public security of the city. Due to the complexity of the underground environment, lack of various monitoring technologies, high cost, backwardness of emergency technology research, incongruity of safety management, and the transport of flammable, explosive, toxic, and harmful hazardous sources to densely populated areas, the boundary between industrial, residential, and living areas has become increasingly blurred, causing a major threat to public security, people's lives, industrial production, and social stability. Traditional underground pipeline accident prevention and control technology is currently unable to meet the increasing demands of public security. Combining pipeline accident prevention and control with internet of things and artificial intelligence technology can achieve urban disaster prevention, and therefore is of great interest to researchers. Herein, the research status of underground pipeline accident prevention and control technology is summarized, and an analysis of the advantages of applying big data for risk factor monitoring, risk assessment, risk early warning, and emergency decision-making technology is discussed. Further, the application difficulties and difficulties regarding big data technology in underground pipeline accident prevention and control and their potential solutions are detailed. Based on the internet of things data, spatiotemporal model mining, and Geographic Information System (GIS), we analyze the distribution and influencing factors of harmful gases in the urban underground sewage pipe network of Chongqing City, and explore the influence of smart city developments on harmful gases in the urban underground sewage pipe network.

城市地下管线结构复杂，使用寿命长，容易受到非法干扰，腐蚀和外力破坏。因此，它们是持续存在的安全风险，严重威胁着城市的公共安全。由于地下环境的复杂性，缺乏各种监测技术，成本高昂，应急技术研究落后，安全管理不力以及易燃，易爆，有毒和有害危险源向人口稠密地区（边界）的运输工业，住宅和居住区之间的距离越来越模糊，对公共安全，人民生活，工业生产和社会稳定构成重大威胁。传统的地下管道事故预防和控制技术目前无法满足公共安全日益增长的需求。将管道事故预防与控制与物联网和人工智能技术相结合可以实现城市防灾，因此对研究人员具有极大的兴趣。本文总结了地下管线事故预防与控制技术的研究现状，并分析了将大数据应用于风险因素监测，风险评估，风险预警和应急决策技术的优势。此外，详细介绍了大数据技术在地下管道事故预防和控制中的应用难点和潜在的解决方案。根据物联网数据，