首页    期刊浏览 2024年11月28日 星期四
登录注册

文章基本信息

  • 标题:Diagnose Urban Drainage Network Problem Based on Internet of Things and Big Data
  • 本地全文:下载
  • 作者:Miao Xiaobo ; Lv Mou ; Liang Fengchao
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2018
  • 卷号:246
  • DOI:10.1051/matecconf/201824602024
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:Urban drainage pipe network is an important foundation project in urban construction. It has a vital impact on urban waterlogging prevention and water pollution. However, in the current practice, there are many hidden problems in the pipe network, and it is difficult to check the pipe network problem, which restricts the understanding of the drainage system problem to a certain extent. In order to solve the two technical problems of drainage network survey and data statistics, the monitoring technology based on Internet of things and big data is adopted in this study. Taking the sponge city pilot area of a coastal city in China as the research area, the monitoring scheme was established and the monitoring data were obtained. Based on more than 6 million monitoring data, the automatic analysis algorithm is applied to analyse the problems of mixed connection of rain and sewage and tidal backwater in the pipeline network. The results show that there are a total of 17 outlets in 160 outlets with problems of rain and sewage mixing. Among them, there are four outlets with regular domestic sewage entering the rainwater pipe network, 7 outlets with irregular sewage entering the rainwater pipe network, and 6 outlets where sewage is smuggled into the rainwater pipe network. In addition, there is a sea tidal backwater phenomenon at one of the coastal rainwater outfalls.
国家哲学社会科学文献中心版权所有