000152188 001__ 152188
000152188 005__ 20251017144555.0
000152188 0247_ $$2doi$$a10.3390/drones9040248
000152188 0248_ $$2sideral$$a143411
000152188 037__ $$aART-2025-143411
000152188 041__ $$aeng
000152188 100__ $$aMoraga , Álvaro
000152188 245__ $$aAI-Driven UAV and IoT Traffic Optimization: Large Language Models for Congestion and Emission Reduction in Smart Cities
000152188 260__ $$c2025
000152188 5060_ $$aAccess copy available to the general public$$fUnrestricted
000152188 5203_ $$aTraffic congestion and carbon emissions remain pressing challenges in urban mobility. This study explores the integration of UAV (drone)-based monitoring systems and IoT sensors, modeled as induction loops, with Large Language Models (LLMs) to optimize traffic flow. Using the SUMO simulator, we conducted experiments in three urban scenarios: Pacific Beach and Coronado in San Diego, and Argüelles in Madrid. A Gemini-2.0-Flash experimental LLM was interfaced with the simulation to dynamically adjust vehicle speeds based on real-time traffic conditions. Comparative results indicate that the AI-assisted approach significantly reduces congestion and CO2 emissions compared to a baseline simulation without AI intervention. This research highlights the potential of UAV-enhanced IoT frameworks for adaptive, scalable traffic management, aligning with the future of drone-assisted urban mobility solutions.
000152188 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000152188 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000152188 700__ $$ade Curtò, J.
000152188 700__ $$0(orcid)0000-0002-5844-7871$$ade Zarzà, I.$$uUniversidad de Zaragoza
000152188 700__ $$aCalafate, Carlos T.
000152188 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000152188 773__ $$g9, 248 (2025), [28 pp.]$$pDrones (Basel)$$tDrones (Basel)$$x2504-446X
000152188 8564_ $$s20794100$$uhttps://zaguan.unizar.es/record/152188/files/texto_completo.pdf$$yVersión publicada
000152188 8564_ $$s2420165$$uhttps://zaguan.unizar.es/record/152188/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000152188 909CO $$ooai:zaguan.unizar.es:152188$$particulos$$pdriver
000152188 951__ $$a2025-10-17-14:12:53
000152188 980__ $$aARTICLE