Special Session on Computational Intelligence for Internet of Things and Cyber-Physical Systems (IoT-CPS)

The Special Session on Computational Intelligence for Internet of Things and Cyber-Physical Systems (IoT-CPS) will be held in conjunction with IEEE World Congress on Computational Intelligence (IEEE WCCI 2020), to be held in Glasgow, UK, on July 19-24, 2020.


The IoT-CPS special session is in the Cross-Disciplinary & Applications category of IEEE CEC 2020 Conference.

The special session aims to bring researchers together from academia and industry to share the state-of-the art research and development in the areas of Internet of Things (IoT) and Cyber-Physical Systems (CPS) using Computational Intelligence techniques. The main objective of this special session is to invite papers that illustrate new ideas, innovative research results, or systematic reviews in the above mentioned area.

All IoT-CPS 2020 accepted papers will be published by IEEE in IEEEXplore.

Motivation and Scope:

Over the past few years, different Internet of Things (IoT) applications have emerged in various fields, including e-health, smart grid, computer vision, smart city, cyber security, intelligent transportation, etc. According to the National Science Foundation (NSF), the Cyber-Physical Systems (CPS) are ‘engineered systems that are built from, and depend upon, the seamless integration of computational algorithms and physical components.’ CPS is, therefore, considered as a system that is based on computer-based mechanisms connected via the Internet and is easily accessible to the users. Hence, IoT and CPS both refer to integrating network connectivity and digital capabilities with physical devices and engineering systems in order to enhance their performance and functionality. Such systems range from smart grids and intelligent vehicles to wearable devices and advanced manufacturing systems. These advancements in technology create numerous opportunities and trends in sectors ranging from energy and intelligent transportation to agriculture, healthcare, smart cities, autonomous systems, and aerospace applications, etc. However, the massive amount of data generated by sensors and other devices in IoT poses new requirements and challenges such as scalability, configuration flexibility, and robustness that need to be properly addressed.

Computational Intelligence (CI) refers to the theory, design, and application of bio and nature inspired computational systems that focus on solving various kinds of complex problems. Neural Networks, Fuzzy Systems and Evolutionary Computation have been the main pillars of CI systems in addition to a number of other machine learning algorithms. These CI techniques have been successfully used to solve various problems related to IoT and CPS applications. CI techniques have played a major role in providing intelligent solutions to a number of real-world problems.

This special session aims at addressing various challenges posed by IoT-CPS applications using Computational Intelligence techniques that include Neural Networks, Fuzzy Logic, Evolutionary Computation, Deep Learning, Machine Learning, and Data Mining algorithms.

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

  • CI techniques for Big Data applications in IoT/CPS
  • CI for security, privacy, and trust for IoT/CPS
  • CI for mobile edge computing
  • CI for sensor and actuator networks
  • Neural networks for IoT/CPS applications
  • Deep Learning for malware and intrusion detection
  • Deep reinforcement learning for IoT/CPS
  • Development of CI algorithms for IoT/CPS environments
  • Evolutionary computation for IoT/CPS applications
  • Fuzzy logic for IoT/CPS
  • Machine learning for IoT based applications
  • Probabilistic methods for IoT/CPS
  • Multi-Criteria Decision Making for IoT/CPS applications

Special Session Chairs:

Farrukh Aslam Khan, King Saud University, Saudi Arabia (Primary Contact)

Amir Hussain, Edinburgh Napier University, UK

Ali Kashif Bashir, Manchester Metropolitan University, UK

Zahid Anwar, Fontbonne University, USA