Edge-Fog-Cloud Machine Learning for Smart Cities Applications!

Edge-Fog-Cloud Machine Learning for Smart Cities Applications
A Special Session at the European Signal Processing Conference (EUSIPCO) 2022

MARVEL is organizing the “Edge-Fog-Cloud Machine Learning for Smart Cities Applications” a Special Session at the EUSIPCO 2022. The aim of this special session is to bring together and disseminate state-of-the-art research contributions that address Edge-to-fog-to-cloud (E2F2C) processing in the context of smart cities, including the analysis and design of novel algorithms and methodologies, innovative smart cities applications with E2F2C processing, and enabling technologies, etc. Please consider submitting your latest research in the topic.

The special session seeks original contributions and review papers in, but not limited to, the following topics:

  • Distributed machine learning
  • Federated learning
  • Just-in-time deep learning models (e.g. early exiting, dynamic computation graphs)
  • Collaborative Edge Computing with machine/deep learning
  • E2F2C offloading mechanisms
  • Resource-efficient ML/DL at the edge
  • Machine Learning for Internet of Things
  • Multi-modal data analysis (e.g. visual, audio, sensor signals)
  • Applications of machine learning for smart city analytics and decision making
Important Dates
  • February 20, 2022

    Paper submission

  • May 6, 2022

    Notification of acceptance

  • June 5, 2022

    Camera ready paper submission


Please submit your manuscript through the conference main website by following the instructions provided in this link

For more information please visit the event website here



Key Facts

  • Project Coordinator: Dr. Sotiris Ioannidis
  • Institution: Foundation for Research and Technology Hellas (FORTH)
  • E-mail: marvel-info{at}marvel-project.eu 
  • Start: 01.01.2021
  • Duration: 36 months
  • Participating Organisations: 17
  • Number of countries: 12

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This project has received funding from the European Union’s Horizon 2020 Research and Innovation program under grant agreement No 957337. The website reflects only the view of the author(s) and the Commission is not responsible for any use that may be made of the information it contains.