HMS 2019 Call For Papers
Machine Learning and Big Data Applications on E-Mobility
Co-Chairs: (a) Michela Longo, (b) Seyedmahdi Miraftabzadeh, (c) Federica Foiadelli
Affiliation: Politecnico di Milano, Italy;
Contact: (a) michela.longo@polimi.it; (b) seyedmahdi.miraftabzadeh@polimi.it; (c) federica.foiadelli@polimi.it
Track Description
Electric Mobility industry faced different challenges to readjust E-mobility in nowadays life, particularly in smart cities. In the complex vehicle environment, state-of-art technologies are required to consider all essential variables are influencing it while conventional algorithms have limited capabilities for combating such a challenge. This session is dedicated to introducing, reviewing and exploring the applications of Machine Learning and Big Data on E-mobility as promising solutions for future trends
Topics of interest of this special session include, but are not limited to:
- Innovative charging systems.
- G2V and V2G and concepts.
- Integrating EV with Storage and Grids.
- Intelligent transportation management systems.
- Driving condition learning and prediction in vehicular network.
- Battery health prognosis system.
- Range estimation.
Nonetheless, different topics regarding Machine Learning and Big Data Applications on E-Mobility are welcome.
For further information please contact Michela Longo, Seyedmahdi Miraftabzadeh and Federica Foiadelli.
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