Drones-DT: Dynamic Fleet Management of Drones Represented by Digital Twins

• José Miqueias UFPI
• Lucas Silva Lopes UFPI
• Iure Fé UFPI
• Jonas Nunes UFPI
• Luiz Fernando Bittencourt UNICAMP
• Juliano Wickboldt UFRGS
• Francisco Airton Silva UFPI

DOI: https://doi.org/10.5753/sbrc.2026.19309

Abstract

Drone delivery systems have proven to be a promising alternative for urban applications that require speed and operational flexibility. However, the variability of demand makes it difficult to adequately size the fleet, which can result in underutilization of resources or violations of Service Level Agreements (SLAs), especially those related to average delivery time. This work proposes a Digital Twin architecture for the dynamic management of drone fleets, based on a Stochastic Petri Net model. Drones-DT is continuously synchronized with a drone simulator and performs what-if predictive analyses to estimate performance metrics. Based on these estimates, an SLA-driven decision mechanism dynamically adjusts the number of drones in operation. The results indicate that the proposed approach maintains SLA compliance while reducing the average number of drones used when compared to static strategies.

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