{"title":"新兴的无人机智能城市低成本空气质量监测技术","authors":"Piyush Yadav, Tejas Porwal, Vedanta Jha, S. Indu","doi":"10.1109/CONECCT50063.2020.9198487","DOIUrl":null,"url":null,"abstract":"Air quality is a local phenomenon, that is, it changes in a significant manner from point to point, thus making air quality mapping from scarce static air quality sensors, practically insignificant. Thus, air quality monitoring using mobile sources holds enormous potential as it gives us the ability to perform spatiotemporal pollution mapping of a geographically wide region using just a few mobile sensors and at a cost that is almost negligible to ground-based static sensors. Drone technology has emerged as a very important platform to do sensing of various physical phenomena around us and by integrating low-cost and light-weight air quality sensors on a UAV, it is possible to get fine-grained spatiotemporal air quality data to have a better overview of the pollution variation and locate its source of origin. In this study, we have designed and manufactured a fixed-wing solar-powered UAV, with potential to perform perpetual flight using solar power and generate air quality data in real-time. Fixed-wing UAV design was chosen for this study due to less propeller wash on sensor readings and more flight time possible than a quadcopter. This UAV system was successfully field-tested at a low altitude and air quality data was generated on the ground, collecting, storing and transmitting data through a data fusion module consisting of low-cost OPC R1 sensor, Raspberry Pi and Pixhawk Flight controller. We do spatiotemporal analysis of the generated PM 2.5 data from the system, which could be very useful to identify pollution hotspots in urban areas, industrial region, smart cities and locate stubble burning sites.","PeriodicalId":261794,"journal":{"name":"2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"314 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Emerging Low-Cost Air Quality Monitoring Techniques for Smart Cities with UAV\",\"authors\":\"Piyush Yadav, Tejas Porwal, Vedanta Jha, S. Indu\",\"doi\":\"10.1109/CONECCT50063.2020.9198487\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Air quality is a local phenomenon, that is, it changes in a significant manner from point to point, thus making air quality mapping from scarce static air quality sensors, practically insignificant. Thus, air quality monitoring using mobile sources holds enormous potential as it gives us the ability to perform spatiotemporal pollution mapping of a geographically wide region using just a few mobile sensors and at a cost that is almost negligible to ground-based static sensors. Drone technology has emerged as a very important platform to do sensing of various physical phenomena around us and by integrating low-cost and light-weight air quality sensors on a UAV, it is possible to get fine-grained spatiotemporal air quality data to have a better overview of the pollution variation and locate its source of origin. In this study, we have designed and manufactured a fixed-wing solar-powered UAV, with potential to perform perpetual flight using solar power and generate air quality data in real-time. Fixed-wing UAV design was chosen for this study due to less propeller wash on sensor readings and more flight time possible than a quadcopter. This UAV system was successfully field-tested at a low altitude and air quality data was generated on the ground, collecting, storing and transmitting data through a data fusion module consisting of low-cost OPC R1 sensor, Raspberry Pi and Pixhawk Flight controller. We do spatiotemporal analysis of the generated PM 2.5 data from the system, which could be very useful to identify pollution hotspots in urban areas, industrial region, smart cities and locate stubble burning sites.\",\"PeriodicalId\":261794,\"journal\":{\"name\":\"2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)\",\"volume\":\"314 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CONECCT50063.2020.9198487\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONECCT50063.2020.9198487","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Emerging Low-Cost Air Quality Monitoring Techniques for Smart Cities with UAV
Air quality is a local phenomenon, that is, it changes in a significant manner from point to point, thus making air quality mapping from scarce static air quality sensors, practically insignificant. Thus, air quality monitoring using mobile sources holds enormous potential as it gives us the ability to perform spatiotemporal pollution mapping of a geographically wide region using just a few mobile sensors and at a cost that is almost negligible to ground-based static sensors. Drone technology has emerged as a very important platform to do sensing of various physical phenomena around us and by integrating low-cost and light-weight air quality sensors on a UAV, it is possible to get fine-grained spatiotemporal air quality data to have a better overview of the pollution variation and locate its source of origin. In this study, we have designed and manufactured a fixed-wing solar-powered UAV, with potential to perform perpetual flight using solar power and generate air quality data in real-time. Fixed-wing UAV design was chosen for this study due to less propeller wash on sensor readings and more flight time possible than a quadcopter. This UAV system was successfully field-tested at a low altitude and air quality data was generated on the ground, collecting, storing and transmitting data through a data fusion module consisting of low-cost OPC R1 sensor, Raspberry Pi and Pixhawk Flight controller. We do spatiotemporal analysis of the generated PM 2.5 data from the system, which could be very useful to identify pollution hotspots in urban areas, industrial region, smart cities and locate stubble burning sites.