Alfa Budiman, Wenbo Wu, Edisson A. Naula-Duchi, Patricia Portillo Jiménez, Hanifeh Imanian, P. Payeur, Luis E. GarzaCastañón, A. Mohammadian, E. Lanteigne
{"title":"Dynamic Sensor Nodes Distribution with Coordinated Autonomous Vehicles for Environment Pollution Monitoring and Modeling","authors":"Alfa Budiman, Wenbo Wu, Edisson A. Naula-Duchi, Patricia Portillo Jiménez, Hanifeh Imanian, P. Payeur, Luis E. GarzaCastañón, A. Mohammadian, E. Lanteigne","doi":"10.11159/rtese23.122","DOIUrl":null,"url":null,"abstract":"– This research aims toward collecting air and water samples over opportunistically selected locations to monitor pollutants distribution. To support precise sensor nodes deployment over a variety of terrains and changing conditions, not only appropriate sensor devices must be designed, but means for deployment must also be carefully studied, developed, and implemented. This paper investigates methodologies to efficiently distribute environment sensor nodes while maximizing space coverage, minimizing acquisition time, and leveraging the benefits of autonomous robotic agents to carry environmental sensors to strategic locations. The research contributes to fill existing gaps in local and global sensor networks for environment pollution monitoring by developing innovative technologies to dynamically deploy sensor nodes using mobile unmanned ground, air and water vehicles. The dispatch of dynamic sensor nodes on autonomous robotic agents to collect measurements on pollution can efficiently cover territories of different size, automatically detect areas where pollution varies significantly or reaches concerning levels, and strategically concentrate data acquisition over those regions to support the formation of more accurate data-centric pollutants dispersion models.","PeriodicalId":308370,"journal":{"name":"International Conference of Recent Trends in Environmental Science and Engineering","volume":"21 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference of Recent Trends in Environmental Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11159/rtese23.122","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
– This research aims toward collecting air and water samples over opportunistically selected locations to monitor pollutants distribution. To support precise sensor nodes deployment over a variety of terrains and changing conditions, not only appropriate sensor devices must be designed, but means for deployment must also be carefully studied, developed, and implemented. This paper investigates methodologies to efficiently distribute environment sensor nodes while maximizing space coverage, minimizing acquisition time, and leveraging the benefits of autonomous robotic agents to carry environmental sensors to strategic locations. The research contributes to fill existing gaps in local and global sensor networks for environment pollution monitoring by developing innovative technologies to dynamically deploy sensor nodes using mobile unmanned ground, air and water vehicles. The dispatch of dynamic sensor nodes on autonomous robotic agents to collect measurements on pollution can efficiently cover territories of different size, automatically detect areas where pollution varies significantly or reaches concerning levels, and strategically concentrate data acquisition over those regions to support the formation of more accurate data-centric pollutants dispersion models.