{"title":"A real time urban flood monitoring system for metro Manila","authors":"Felan Carlo C. Garcia, A. Retamar, Joven Javier","doi":"10.1109/TENCON.2015.7372990","DOIUrl":null,"url":null,"abstract":"A real time urban flood monitoring system was deployed into two streets (Earnshaw and San Diego Streets) on España Boulevard, Manila. The system consists of a ground-based pressure sensor and a rain gauge connected to a locally designed data logger with telemetry capabilites using GPRS network. Data from the stations are received by a TCP server and is processed in order to provide visual information and realtime flood updates through mobile and web services. An ahead of time flood estimation system was implemented using a Random Forest algorithm in order to provide an early warning advisory to motorist and users of the system. Results from the test validation show that the resulting prediction model indicates a strong predictive performance without relying on rainfall-runoff model obtained through geological and hydrological surveys.","PeriodicalId":22200,"journal":{"name":"TENCON 2015 - 2015 IEEE Region 10 Conference","volume":"95 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"TENCON 2015 - 2015 IEEE Region 10 Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TENCON.2015.7372990","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20
Abstract
A real time urban flood monitoring system was deployed into two streets (Earnshaw and San Diego Streets) on España Boulevard, Manila. The system consists of a ground-based pressure sensor and a rain gauge connected to a locally designed data logger with telemetry capabilites using GPRS network. Data from the stations are received by a TCP server and is processed in order to provide visual information and realtime flood updates through mobile and web services. An ahead of time flood estimation system was implemented using a Random Forest algorithm in order to provide an early warning advisory to motorist and users of the system. Results from the test validation show that the resulting prediction model indicates a strong predictive performance without relying on rainfall-runoff model obtained through geological and hydrological surveys.