Evaluation of Unmanned Aerial Vehicles for Precision Agriculture Based on Integrated Fuzzy Decision-Making Approach

The drone, also known as an unmanned aerial vehicle (UAV), offers significant advantages for precision agriculture by reducing the need for conventional farming practices that require more manpower. The use of drones in agriculture offers significant economic and time-saving benefits. The evaluation of UAVs’ performance is urgently needed in light of their proliferation in agriculture during the past few decades. This evaluation falls under the complex multicriteria decision-making (MCDM) problem due to the existence of multicriteria, criteria importance, and trade-offs or conflicts amongst them. Thus, the main purpose of this study is to offer an integrated fuzzy MCDM approach based on two significant methods. The first method is the fuzzy-weighted zero-inconsistency (FWZIC) method for calculating the UAV criteria (i.e., payload, endurance, and dimensions) weight coefficients. The second method is the fuzzy decision by opinion score method (FDOSM) for UAV alternative selection based on individual and group decision-making (GDM) settings. The decision matrix used in the selection approach of UAV categories is formulated based on the intersection of payload, endurance, and dimensions criteria and the UAV alternatives list. The findings show that (1) the FWZIC has effectively determined the criteria weights with a zero inconsistency rate. The maximum weight value is given to the payload criterion (0.428), whereas the dimension criterion was given the least value weight (0.199). (2) In the context of GDM, FDOSM is used to eliminate the dissimilarity between individual MCDM results across all categories of UAV. Finally, objective validation and sensitivity analysis were utilized to evaluate the strength of UAV selection results.