| Title |
Supervised Learning based Greenery region detection using Unnamed Aerial Vehicle for Smart City Application |
| ID_Doc |
38896 |
| Authors |
Yadav, D; Choksi, M; Zaveri, MA |
| Title |
Supervised Learning based Greenery region detection using Unnamed Aerial Vehicle for Smart City Application |
| Year |
2019 |
| Published |
|
| DOI |
|
| Abstract |
In the urban areas, pollution and over-population are one of the major concern for smart city development. Trees in an urban area are extremely important as they provide shelter, removes air pollutants, reduces water runoff and also provides aesthetic benefits. For environmental planning and management, it is necessary to maintain trees and plants in the city, so accordingly various efforts are taken by the government to regrow plant over a needed area. Unnamed Aerial Vehicle (UAV) based Remote sensing technology can efficiently handle the management and monitoring of green resources with the help of operational methods. But most of the algorithms developed using UAV are for specific spices of trees. The proposed algorithm performs real time data collection using UAV, in which UAV act as an IoT node. The paper presents an efficient algorithm for the detection of green areas and it works for almost all kind of trees. |
| Author Keywords |
Unmanned Aerial Vehicles; greenery region; Smart Cities; Supervised Learning |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000525828100128 |
| WoS Category |
Computer Science, Hardware & Architecture; Telecommunications |
| Research Area |
Computer Science; Telecommunications |
| PDF |
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