A Hybrid Multi-Criteria Decision-Making Approach for Sustainable Forest Fire Monitoring Using Unmanned Aerial Vehicles

Authors

Mohamed Eassa, Computer Science Department, Faculty of Information Systems and Computer Science, October 6 University, EgyptFollow
Ahmed Abdelhafeez, Faculty of Computers and Information Technology, Innovation University, Cairo, Egypt AND Applied Science Research Center, Applied Science Private University, Amman, JordanFollow
Ahmad M. Nagm, Faculty of Computers and Information Technology, Innovation University, Cairo, Egypt AND Department of Computer Engineering and Electronics, Cairo Higher Institute for Engineering, Computer Science and Management, New Cairo, EgyptFollow

Authors' ORCIDs

Mohamed Eassa: https://orcid.org/0000-0001-5011-7969

Ahmed Abdelhafeez: https://orcid.org/0000-0001-6983-5645

Ahmad M. Nagm: https://orcid.org/0000-0003-1801-0381

Article Type

Research Article

Abstract

Unmanned aerial vehicles (UAVs) have become an effective tool for forest fire monitoring. This study evaluates UAVs for forest fire management, addressing the challenges posed by ambiguous and uncertain factors. Single-valued neutrosophic sets (SVNSs) are employed to model complex uncertainties, as they incorporate three distinct membership values: false, true, and indeterminate. The evaluation of UAVs is a multifaceted task due to the variety of factors involved. To address this complexity, multi-criteria decision-making (MCDM) methods are used. Specifically, the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are integrated with SVNS to compute UAV factor weights (via AHP) and rank the UAVs (via SVN-TOPSIS). This study examines sixteen criteria for evaluating ten UAVs to identify the optimal one for forest fire monitoring. A sensitivity analysis is conducted to assess the stability of the results, varying criteria weights and observing their impact on the rankings. The findings confirm the robustness of the proposed methodology, with stable outcomes across different scenarios. A comparative analysis with other MCDM methods (such as CODAS, VIKOR, COPRAS, MABAC, and a fuzzy framework) shows a strong correlation between the results from the proposed model and those from the alternative MCDM approaches.

Keywords

Unmanned aerial vehicles (UAVs), Forest fire monitoring, Multi-criteria decision-making (MCDM), Risk assessment, Sustainability, Environmental monitoring

How to Cite

Eassa, Mohamed; Abdelhafeez, Ahmed; and Nagm, Ahmad M. (2026) "A Hybrid Multi-Criteria Decision-Making Approach for Sustainable Forest Fire Monitoring Using Unmanned Aerial Vehicles," Neutrosophic Systems with Applications: Vol. 26: Iss. 3, Article 5. DOI: https://doi.org/10.63689/2993-7159.1330