Drone Technology for Rice Agriculture at the Fertilizer Spraying Process
| dc.contributor.author | Amarasinghe, Akarshani | |
| dc.contributor.author | Jayaratne, Lakshman | |
| dc.contributor.author | Wijesuriya, Viraj B. | |
| dc.date.accessioned | 2022-02-25T04:02:52Z | |
| dc.date.available | 2022-02-25T04:02:52Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | This paper presents a drone simulator to spray fertilizer for rice farmland with minimum human intervention. The proposed drone simulator is capable of suggesting the optimal path to spray fertilizer, indicating the current altitude and the current battery level of the drone at flight. The obtained results at the evaluation stage show that the proposed path planning algorithm outputs the optimal path for given farmland with minimum execution time. This solution will cherish the use of drone technology for rice agriculture while supporting the economic growth of a country. | en_US |
| dc.identifier.citation | Amarasinghe Akarshani, Jayaratne Lakshman, Wijesuriya Viraj B. (2021), Drone Technology for Rice Agriculture at the Fertilizer Spraying Process, International Conference on Advances in Computing and Technology (ICACT–2021) Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka 76-81 | en_US |
| dc.identifier.uri | http://repository.kln.ac.lk/handle/123456789/24499 | |
| dc.publisher | Faculty of Computing and Technology (FCT), University of Kelaniya, Sri Lanka | en_US |
| dc.subject | drone simulator, q-learning, path planning algorithm | en_US |
| dc.title | Drone Technology for Rice Agriculture at the Fertilizer Spraying Process | en_US |
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