{"title":"Design and Implementation of an Ambient Data Collection Mechanism Based on a Quadcopter","authors":"Yueh-Min Huang, Yu-Yun Chen, Jui-Hung Chang","doi":"10.1109/IC3.2018.00017","DOIUrl":null,"url":null,"abstract":"At present, there are two kinds of data collection methods of most environmental sensor networks, one is static data collection, the sensing points are placed in fixed positions, the sense data are fed back to the database via wireless or wired network and stored. As for the other one, in order to collect data where the network is underdeveloped, the on-board system moves to the region and collect the environmental data. However, the two data collection methods have space constraint. Taking observation on air pollutant as an example, more and more countries reduce the external cost resulted from air pollution actively in recent years. In order to attain this goal, the generation of pollutants must be prevented. Therefore, the pollutant data of 3D space are required for tracing the source of pollutants, only reducing the discharge of toxic substances from the source can improve the air quality. The aforesaid two methods have constraints. In order to attain this goal, this paper uses a quadcopter as aerial vehicle to collect the environmental data at different heights, including temperature, humidity and PM2.5 concentration, which are sent to the database via wireless transmission module, and the data are displayed on visualized webpage. Finally, the relevance analysis is implemented for the data at different heights.","PeriodicalId":236366,"journal":{"name":"2018 1st International Cognitive Cities Conference (IC3)","volume":"4 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 1st International Cognitive Cities Conference (IC3)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3.2018.00017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
At present, there are two kinds of data collection methods of most environmental sensor networks, one is static data collection, the sensing points are placed in fixed positions, the sense data are fed back to the database via wireless or wired network and stored. As for the other one, in order to collect data where the network is underdeveloped, the on-board system moves to the region and collect the environmental data. However, the two data collection methods have space constraint. Taking observation on air pollutant as an example, more and more countries reduce the external cost resulted from air pollution actively in recent years. In order to attain this goal, the generation of pollutants must be prevented. Therefore, the pollutant data of 3D space are required for tracing the source of pollutants, only reducing the discharge of toxic substances from the source can improve the air quality. The aforesaid two methods have constraints. In order to attain this goal, this paper uses a quadcopter as aerial vehicle to collect the environmental data at different heights, including temperature, humidity and PM2.5 concentration, which are sent to the database via wireless transmission module, and the data are displayed on visualized webpage. Finally, the relevance analysis is implemented for the data at different heights.