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The rapid propagation of fires and the need for dynamic resource allocation make fire monitoring a complex and critical challenge. This study presents the modeling and performance evaluation of a fire monitoring system using Stochastic Petri Nets (SPN). The proposed model accurately represents the operational dynamics of a real system, enabling the analysis of key performance metrics, including mean response time (MRT), throughput (TP), drop probability (DP), and resource utilization. Additionally, a sensitivity analysis based on Design of Experiments (DoE) is conducted to identify the most influential factors affecting system performance. Statistical validation showed agreement between the SPN model and the real system (MRT = 1.2013 vs. 1.2016; p-value = 0.9528). In the performance analysis, CFC = 4 kept MRT below 1.40, achieved throughput of about 2.10 pkgs\/s, and reduced drop probability, which reached up to 80% with CFC = 1 under high load. These results underscore the applicability of SPN modeling as a robust methodology for optimizing fire monitoring and response strategies, ultimately contributing to the mitigation of wildfire impacts.<\/jats:p>","DOI":"10.1007\/s10586-026-06147-0","type":"journal-article","created":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T14:37:18Z","timestamp":1781534238000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Optimizing wildfire response: an SPN-based approach to performance and sensitivity analysis"],"prefix":"10.1007","volume":"29","author":[{"given":"Arthur","family":"Sabino","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luiz Nelson","family":"Lima","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vandirleya","family":"Barbosa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leonardo","family":"Freitas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Priscila Solis","family":"Barreto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcos F.","family":"Caetano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francisco Airton","family":"Silva","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,15]]},"reference":[{"issue":"10","key":"6147_CR1","doi-asserted-by":"publisher","first-page":"5377","DOI":"10.5194\/essd-17-5377-2025","volume":"17","author":"DI Kelley","year":"2025","unstructured":"Kelley, D.I., Burton, C., Di Giuseppe, F., Jones, M.W., Barbosa, M.L., Brambleby, E., McNorton, J.R., Liu, Z., Bradley, A.S., Blackford, K.: State of wildfires 2024\u20132025. 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