Workshop on Sensor Data Fusion and Machine Learning for next Generation of Cyber-Physical-Systems

Co-located with ACM International Conference on Computing Frontiers 2018

May 10th, 2018, Ischia, Italy


Start is 30 minutes earlier!


This Workshop provides latest achievements in sensor and information data fusion (IFU)  and machine learning (ML) for cyber-physical-systems. The automotive industry, the process industry, robotics and many others adopted methodologies from IFU and ML which have never been used before. The workshop opens the floor for discussions with academic and industrial representatives who are involved in this next generation of system and application design.

The Workshop targets presentations within the following fields of Research:
  • Algorithms and methods for sensor data fusion and / or machine learning
  • Machine Learning / Sensor data fusion for IoT
  • Machine Learning / Sensor data fusion for Cyberphysical Systems
  • Reconfigurable Hardware deployment for Sensor data fusion and / or Machine Learning
  • Novel Hardware architectures for machine Learning and sensor data fusion
  • Industrial applications using sensor data fusion and machine learing


  • Prof. Dr.-Ing. habil. Michael Huebner, Chair for Embedded Systems (ESIT), Ruhr-University Bochum (RUB), Twitter @esitatrub

Important Dates

  • Paper submission deadline:
    • February 23rd 2018, Midnight CET
  • Notification of acceptance:
    • March16th, 2018, Midnight CET
  • Camera-ready version:
    • March 31st, midnight (sharp Deadline!)
  • Date of the workshop (one day):
    • Thursday, May 10th, 2018


    • Papers must be submitted through the Workshop submission Website
      Full papers are a maximum of eight (8) double-column pages in ACM conference format with an option for authors to buy up to 2 extra pages after acceptance. These limits include figures, tables, and references. The template can be found with this link
    • Our review process is double-blind: please remove all identifying information from the paper submission (and cite your own work in the third person). Papers will be published in the proceedings and in the ACM Digital Library.


     9:15-09:30 Welcome and Introduction
     Michael Hübner

    Shengwei Luo, Chunhui Zhao, Limin Lu and Yongji Fu


    Machine Learning Application for Patients Activity Recognition with Pressure Sensing in Bed


    Hendrik Laux, Andreas Bytyn, Gerd Ascheid, Anke Schmeink, Gunes Karabulut Kurt and Guido Dartmann


    Learning-Based Indoor Localization for Industrial Applications


    11:00-11:30 Coffee Break

    Christoph-Alexander Holst and Volker Lohweg


    Supporting Sensor Orchestration in Non-Stationary Environments


    Yuling Luo, Qian Lu, Junxiu Liu, Qiang Fu, Jim Harkin, Mcdaid Liam, Jordi Martínez-Corral and Guillermo Biot-Marí


    Forest Fire Detection using Spiking Neural Networks


    Daniel Hinkelmann, Anke Schmeink and Guido Dartmann


    Distributed learning-based state prediction for multi-agent systems with reduced communication effort