Name
Title | ||
|---|---|---|
Federated Learning in the Sky: Aerial-Ground Air Quality Sensing Framework with UAV Swarms |
Abstract | ||
|---|---|---|
Due to air quality significantly affects human health, it is becoming increasingly important to accurately and timely predict the air quality index (AQI). To this end, this article proposes a new federated learning (FL)-based aerial-ground air quality sensing framework for fine-grained 3-D air quality monitoring and forecasting. Specifically, in the air, this framework leverages a lightweight Dens... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/JIOT.2020.3021006 | IEEE Internet of Things Journal |
Keywords | DocType | Volume |
Monitoring,Sensors,Atmospheric modeling,Air quality,Data models,Unmanned aerial vehicles,Three-dimensional displays | Journal | 8 |
Issue | ISSN | Citations |
12 | 2327-4662 | 9 |
PageRank | References | Authors |
0.44 | 14 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liu Yi | 1 | 82 | 4.78 |
| Jiangtian Nie | 2 | 97 | 10.96 |
| Xuandi Li | 3 | 18 | 0.90 |
| Syed Hassan Ahmed | 4 | 505 | 65.70 |
| Wei Yang Lim | 5 | 193 | 13.37 |
| Chunyan Miao | 6 | 2307 | 195.72 |