Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/4CFD9BC4-2481-4866-85B4-4875B4D013CB | ||
| Year | 2025 | ||
| Type of Item | Master Thesis | ||
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| Bibliographic Citation | Ευαγγελία Άννα Παπαϊωάννου, "Σχεδιασμός τροχιάς μη επανδρωμένων αεροσκαφών για εφαρμογές γεωργίας ακριβείας", Μεταπτυχιακή Διατριβή, Σχολή Μηχανικών Παραγωγής και Διοίκησης, Πολυτεχνείο Κρήτης, Στρατιωτική Σχολή Ευελπίδων, Χανιά, Ελλάς, 2025 https://doi.org/10.26233/heallink.tuc.103859 | ||
| Appears in Collections |
Precision Agriculture (PA) is a relatively modern approach to pesticide spraying, playing a crucial role in ensuring the health of crops and by extension their yields. Today, Unmanned Aerial Vehicles (UAVs) are used extensively for this purpose, leading to prudent use of pesticides, while balancing costs and environmental conservation. Based on the above, the need arose to create an integrated optimal trajectory system for use in PA with tools from graph theory. For this purpose, after initially conducting an extensive theoretical analysis of the tools used (Normalized Difference Vegetation Index-NDVI, Visibility graph-VG, Dijkstra Algorithm, Floyd-Warshall Algorithm, Genetic Algorithm-GA) as well as the wayin which they are connected to each other, codes were then created with the combination of the above tools. Specifically, 3 scenarios were created to find the optimal route for 3 different agricultural plots (wheat, cotton, faba bean) where each scenario was evaluated according to the Euclidean Distance, theNDVI or a combination of these 2 metrics. From the above, the conclusion emerged that the combination of both metrics for finding the optimal route gives better results compared to those from each metric separately. However, despite the positive results, it deserves more investigation as there is no literature that directly proves the effectiveness of these 2 metrics.
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