1 October, 2019

SS07 – Soft-computing and Machine Learning in IoT, Big Data and Cyber Physical Systems


New sensors and network capabilities have enhanced the use of technology in a wide spread of fields, such as petroleum ducts, health services, education, factories, etc. The data availability has become a new problem, where Big Data technologies focus in the management and visualization of relevant information within the data flow. Furthermore, Machine Learning and Soft-Computing are techniques that have allow to extract knowledge from these streams of data. This special session focuses on solutions to all these problems and technologies, accepting studies that deals with IoT systems, Big Data solutions, Cyber Physical problems and the use of Soft-Computing and Machine Learning applied in these scenarios.

The goal of this special session is to provide a platform for researchers, engineers, and industrial practitioners from different fields to share and exchange their ideas, research results, and experiences in the field of AI Advances and developments in IoT, Big Data, and Cyber-Physical Systems (CPS). Contributions to this special session are welcome to present novel methods, algorithms, frameworks, architectures, platforms, and applications.


Potential topics of interest include, but are not limited to the following:

  • Advances in AI, Machine Learning, Deep Learning
  • Testing and validation of AI applications
  • Risks, limitations, and challenges of AI
  • Smart cities and autonomous robots
  • Telepresence robots and IoT-based CPS
  • Architecture design and development of smart systems
  • Standards, protocols, and methodologies for CPS and IoT
  • Context-aware sensing and computing in IoT-based CPS
  • CPS and wearable devices tracking
  • Remote monitoring and interoperability in IoT  AI and Big Data developments in life quality and healthcare
  • Ambient intelligence and intelligent platforms for collaborative test-beds
  • Open IoT platforms for modeling, simulation, and testing
  • AI for IoT and CPS applications in environmental monitoring, transportation, and healthcare
  • AI and CPS applications in Industry 4.0
  • Big Data Analytics
  • Human-Machine Interaction
  • AI for IoT and Cloud Computing Integration

Session Chairs

  • José Ramón Villar, University of Oviedo (Spain)
  • Nashwa El-Bendary, Arab Academy for Science, Technology & Maritime Transport (Egypt)
  • Qing Tan, School of Computing and Information Systems, Athabasca University



Prof. José Ramón Villar

Computer Science Department, University of Oviedo

West Departmental Building, Campus de Viesques s/n 33204 Gijón (Spain)

E-mail: villarjose@uniovi.es