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dc.contributor.authorMoraga, Álvaroes-ES
dc.contributor.authorde Curtò i Díaz, Joaquimes-ES
dc.contributor.authorde Zarzà i Cubero, Irenees-ES
dc.contributor.authorCalafate, Carlos T.es-ES
dc.date.accessioned2025-03-26T15:51:08Z
dc.date.available2025-03-26T15:51:08Z
dc.date.issued2025-03-26es_ES
dc.identifier.issn2504-446Xes_ES
dc.identifier.urihttps://doi.org/10.3390/drones9040248es_ES
dc.descriptionArtículos en revistases_ES
dc.description.abstract.es-ES
dc.description.abstractTraffic 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 Gemini2.0-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 solutionsen-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.rightsCreative Commons Reconocimiento-NoComercial-SinObraDerivada Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/es_ES
dc.sourceRevista: Drones, Periodo: 1, Volumen: 9, Número: 4, Página inicial: 248, Página final: .es_ES
dc.titleAI-Driven UAV and IoT Traffic Optimization: Large Language Models for Congestion and Emission Reduction in Smart Citieses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.description.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.rights.holderes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.keywords.es-ES
dc.keywordstraffic optimization; IoT; large language models; SUMO; smart mobility; AI-driven traffic control; urban congestion; CO2 emission reduction; UAV; drone-assisted traffic managementen-GB


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