{"title":"马尼拉大都会的实时城市洪水监测系统","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":"{\"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}","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}
A real time urban flood monitoring system for metro Manila
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.