{"title":"CDME -众包数据映射引擎系统,分析,mapps和发布环境事实的众包数据","authors":"S. Ruwanpathirana, I. Perera","doi":"10.1109/MERCON.2015.7112358","DOIUrl":null,"url":null,"abstract":"Availability of records on environmental factors like noise, temperature, and precipitation is important in making critical decisions concerning public safety and wellbeing. Traditional methods involving dedicated human personnel and equipment in capturing these data have been reliable, but extremely costly and time consuming. We propose a data collecting and visualizing framework based on crowd sourcing that is readily available, extensible, and virtually incurs zero cost. The crowd-sourced data mapping engine (CDME) presents an extensible back-end web application and a noise data collecting mobile application targeting analyses on noise pollution, which poses a significant concern especially in urban areas. The mobile applications runs as a service and updates the server with periodic noise data. The server accepts data updates and provides analytical functions such as graphs and heat maps.","PeriodicalId":373492,"journal":{"name":"2015 Moratuwa Engineering Research Conference (MERCon)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"CDME — crowd-sourced data mapping engine system that analyzes, mapps & publishes crowd-sourced data on enviorenment facts\",\"authors\":\"S. Ruwanpathirana, I. Perera\",\"doi\":\"10.1109/MERCON.2015.7112358\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Availability of records on environmental factors like noise, temperature, and precipitation is important in making critical decisions concerning public safety and wellbeing. Traditional methods involving dedicated human personnel and equipment in capturing these data have been reliable, but extremely costly and time consuming. We propose a data collecting and visualizing framework based on crowd sourcing that is readily available, extensible, and virtually incurs zero cost. The crowd-sourced data mapping engine (CDME) presents an extensible back-end web application and a noise data collecting mobile application targeting analyses on noise pollution, which poses a significant concern especially in urban areas. The mobile applications runs as a service and updates the server with periodic noise data. The server accepts data updates and provides analytical functions such as graphs and heat maps.\",\"PeriodicalId\":373492,\"journal\":{\"name\":\"2015 Moratuwa Engineering Research Conference (MERCon)\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Moratuwa Engineering Research Conference (MERCon)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MERCON.2015.7112358\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Moratuwa Engineering Research Conference (MERCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MERCON.2015.7112358","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
CDME — crowd-sourced data mapping engine system that analyzes, mapps & publishes crowd-sourced data on enviorenment facts
Availability of records on environmental factors like noise, temperature, and precipitation is important in making critical decisions concerning public safety and wellbeing. Traditional methods involving dedicated human personnel and equipment in capturing these data have been reliable, but extremely costly and time consuming. We propose a data collecting and visualizing framework based on crowd sourcing that is readily available, extensible, and virtually incurs zero cost. The crowd-sourced data mapping engine (CDME) presents an extensible back-end web application and a noise data collecting mobile application targeting analyses on noise pollution, which poses a significant concern especially in urban areas. The mobile applications runs as a service and updates the server with periodic noise data. The server accepts data updates and provides analytical functions such as graphs and heat maps.