| Title | AQ360: UAV-Aided Air Quality Monitoring by 360-Degree Aerial Panoramic Images in Urban Areas |
| Authors | Gao, Jiahao Hu, Zhiwen Bian, Kaigui Mao, Xinyu Song, Lingyang |
| Affiliation | Peking Univ, Sch Elect Engn & Comp Sci, Natl Engn Lab Big Data Anal & Applicat, Beijing 100871, Peoples R China Peking Univ, State Key Lab Adv Opt Commun Syst & Networks, Beijing 100871, Peoples R China |
| Issue Date | 1-Jan-2021 |
| Publisher | IEEE INTERNET OF THINGS JOURNAL |
| Abstract | Driven by the increasingly serious air pollution problem, nowadays different systems can be used to achieve the monitoring task of air quality index (AQI) in urban areas. In this article, we design a novel unmanned aerial vehicle-aided (UAV-aided) AQI monitoring system, called AQ360, which detects the air quality level from the 360-degree aerial panoramic images taken by the onboard camera. Specifically, we first present our own AQI recognition approach based on the physical form of the haze pictures, where the AQI is jointly decided by the images captured along six directions over the target location. Then, we study the UAV placement problem of selecting UAV's flight altitude and 2-D coordinates during the monitoring process. The objective is to save the system energy consumption while maintaining the accuracy of estimating AQI distribution. For practical considerations, we implement and evaluate the proposed system in real-world scenarios. The results show that our system can provide a lower AQI recognition error compared with existing vision-based monitoring approaches, and energy consumption is also reduced when applying for large-area tasks. |
| URI | http://hdl.handle.net/20.500.11897/602176 |
| ISSN | 2327-4662 |
| DOI | 10.1109/JIOT.2020.3004582 |
| Indexed | EI SCI(E) |
| Appears in Collections: | 信息科学技术学院 其他实验室 区域光纤通信网与新型光通信系统国家重点实验室 |
