Autonomous Drone System for Afforestation with Swarm Intelligence
| dc.contributor.author | Yildirim, B.E. | |
| dc.contributor.author | Durmaz, S. | |
| dc.contributor.author | Yildiz, A. | |
| dc.contributor.author | Kucukkomurcu, B. | |
| dc.contributor.author | Ozbek, T. | |
| dc.contributor.author | Türkmen, G. | |
| dc.date.accessioned | 2026-03-05T15:08:13Z | |
| dc.date.available | 2026-03-05T15:08:13Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | This project explores tree detection and tracking using drones coordinated by swarm intelligence. By enabling autonomous coordination and real-time communication between multiple drones, swarm-based systems significantly enhance area coverage, reduce redundancy, and increase data reliability compared to traditional single-drone approaches. Drones equipped with high-resolution cameras collect aerial imagery, which is then processed through image analysis and machine learning algorithms to identify tree locations accurately. Dynamic task allocation and route optimization enable efficient regional coverage while minimizing error rates. The entire system is developed and evaluated in a simulation environment, allowing for controlled testing and iterative refinement of the swarm behaviors. This framework offers scalable and adaptive solutions for applications in forest conservation, environmental monitoring, and ecosystem management. © 2025 IEEE. | en_US |
| dc.identifier.doi | 10.1109/UBMK67458.2025.11206903 | |
| dc.identifier.isbn | 9798331599768 | |
| dc.identifier.issn | 2521-1641 | |
| dc.identifier.scopus | 2-s2.0-105030815191 | |
| dc.identifier.uri | https://doi.org/10.1109/UBMK67458.2025.11206903 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14411/11207 | |
| dc.language.iso | en | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
| dc.relation.ispartof | International Conference on Computer Science and Engineering, UBMK -- 10th International Conference on Computer Science and Engineering, UBMK 2025 -- 2025-09-17 Through 2025-09-21 -- Istanbul -- 214243 | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Drone Technology | en_US |
| dc.subject | Environmental Monitoring | en_US |
| dc.subject | Machine Learning | en_US |
| dc.subject | Swarm Intelligence | en_US |
| dc.subject | Tree Detection | en_US |
| dc.title | Autonomous Drone System for Afforestation with Swarm Intelligence | en_US |
| dc.type | Conference Object | en_US |
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| gdc.description.department | Atılım University | en_US |
| gdc.description.departmenttemp | [Yildirim] Bahattin Eren, Atilim University, Ankara, Turkey; [Durmaz] Sena, Atilim University, Ankara, Turkey; [Yildiz] Arda Ertan, Atilim University, Ankara, Turkey; [Kucukkomurcu] Buse, Atilim University, Ankara, Turkey; [Ozbek] Turkay, Atilim University, Ankara, Turkey; [Türkmen] Güzin, Atilim University, Ankara, Turkey | en_US |
| gdc.description.endpage | 1506 | en_US |
| gdc.description.issue | 2025 | en_US |
| gdc.description.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
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| gdc.description.startpage | 1503 | en_US |
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