| Title | Arms: A Fine-Grained 3D AQI Realtime Monitoring System by UAV |
| Authors | Yang, Yuzhe Zheng, Zijie Bian, Kaigui Jiang, Yun Song, Lingyang Han, Zhu |
| Affiliation | School of Electrical Engineering and Computer Science, Peking University, Beijing, China Electrical and Computer Engineering Department, University of Houston, Houston, TX, United States |
| Issue Date | 2018 |
| Publisher | 2017 IEEE Global Communications Conference, GLOBECOM 2017 |
| Citation | 2017 IEEE Global Communications Conference, GLOBECOM 2017. 2018, 2018-January, 1-6. |
| Abstract | Recently, mobile devices have been used to carry sensors to monitor air quality index (AQI), and help construct an AQI map in 2-dimensional (2D) areas. In this paper, we design a novel 3-dimensional (3D) AQI monitoring system, called Arms (AQI realtime monitoring system), to efficiently build realtime fine-grained 3D AQI maps, with the help of unmanned-aerial-vehicles (UAVs). Based on the data monitored by Arms, a novel dispersion model, namely Adaptive Gaussian Plume Model (AGPM) is proposed to predict the distribution of AQI. Moreover, the adaptive monitoring techniques, i.e., complete and optimized monitoring, are designed to effectively produce and maintain realtime AQI maps, while greatly reducing the measurement efforts. Experimental results verify that Arms can provide higher predicting accuracy of AQI with the proposed AGPM than other existing models. In addition, the whole system's battery consumption can be greatly reduced. © 2017 IEEE. |
| URI | http://hdl.handle.net/20.500.11897/530744 |
| ISSN | 9781509050192 |
| DOI | 10.1109/GLOCOM.2017.8253968 |
| Indexed | EI |
| Appears in Collections: | 信息科学技术学院 |
