PhD " API-based approach for E2E green connected mobility " F/M
Orange
- Belfort, Territoire-de-Belfort
- Stage
- Temps-plein
In a world transitioning towards more sustainable and connected solutions, the emergence of connected green mobility represents a major challenge. This evolution is driven by the need to reduce greenhouse gas emissions while offering efficient and integrated transportation solutions. The research context is based on the increasing demand for energy optimization in 5G-V2X networks, resulting from the convergence of telecommunications technologies and connected vehicles. The central problem lies in the complex management of energy consumption across various network elements and vehicles, while ensuring optimal performance. Thus, there is a need to develop innovative strategies to minimize energy consumption while maintaining high service levels.Scientific Objective - Results and Challenges to Address
The objective of the thesis is to develop an API-based approach for connected green mobility, aiming to optimize energy efficiency throughout the vehicle's journey using AI models capable of accurately predicting energy consumption in green V2X networks, considering operational and mobility constraints. This involves addressing challenges such as modeling energy consumption patterns, optimizing AI algorithms for precise consumption prediction, and seamlessly integrating mobility services into existing infrastructure. Expected results include the design of innovative models and the identification of key parameters influencing energy consumption for scalable connected green mobility. This will guide future energy optimization strategies, and ultimately, the exposure of these results through APIs.References[1] Ilhem Souissi, Rihab Abidi, Nadia Ben Azzouna, Tahar Berradia, Lamjed Ben Said, « ECOTRUST: A novel model for Energy COnsumption TRUST assurance in electric vehicular networks », Ad Hoc Networks, Volume 149, 2023,[2] B. Mao, F. Tang, Y. Kawamoto and N. Kato, "AI Models for Green Communications Towards 6G," in IEEE Communications Surveys & Tutorials, vol. 24, no. 1, pp. 210-247, First quarter 2022, doi: 10.1109/COMST.2021.3130901.[3] Lv, Zhihan, and Wenlong Shang. "Impacts of intelligent transportation systems on energy conservation and emission reduction of transport systems: A comprehensive review." Green Technologies and Sustainability (2022).about you
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