Collaborative Intelligent Systems and Applications Regular Track


Weiming Shen (NRC, Canada)
Makoto Itoh (University of Tsukuba, Japan)
Liang Gao (Huazhong University of Science and Technology, Canada)


IoT-Enabled Data-Driven Collaborative Intelligent Systems

Internet of Things (IoT) has been widely accepted as a novel paradigm that can radically transform the industry and our society. It can realize the seamless integration of various devices equipped with sensing, identification, processing, communication, actuation, and networking capabilities. On the other hand, Big Data has recently been considered as a promising technology and become a very active research area primarily involving topics related to machine learning, database, and distributed computing. IoT and Big Data bring great opportunities to improve collaborative intelligent systems which have been proposed, developed, and deployed during the past decades. However, these new technologies also bring significant challenges and do not address major existing issues including system reliability, security, efficiency, and trust management. Significant R&D efforts are required before these technologies can be widely deployed in industrial applications. This regular track aims at addressing the advances on the development of scientific and engineering foundations, innovative technologies and solutions for IoT-enabled data-driven collaborative intelligent systems. It covers the following topics (including, but not limited to):
  • Agent-based collaborative intelligent systems and applications
  • Big Data in collaborative intelligent cyber-physical systems
  • Blockchains for collaborative intelligent systems
  • Collaborative product design methods and systems
  • Cybersecurity in collaborative intelligent cyber-physical systems
  • Development of smart / intelligent products with embedded intelligence
  • Human-centric / customer-oriented product design
  • Human-machine interactions, human-robot / robot-robot collaboration
  • Preventative and predictive equipment maintenance
  • Sensor-fusion for intelligent machining and inspection
  • Smart grids, smart cars, smart homes, smart buildings, smart hospitals, smart cities, …
  • Smart factories, supply chains and logistics
  • Wireless sensor networks, Internet of Things, Industry 4.0

Potential TPC Members:

  • Robert Brennan, U Calgary, Canada
  • Naoufel Cheikhrouhou, EPFL, Switzerland
  • Chin-Hsing Chu, National Tsing Hua U, Taiwan
  • Jean-Marc Frayret, U Montreal, Canada
  • Ricardo Goncalves, UNINOVA, Portugal
  • Soonhung Han, KAIST, Korea
  • George Huang, University of Hong Kong, China
  • Xiaoping Li, Southeast U, China 
  • Weidong Li, Coventry U, UK 
  • Tie Qiu, Tianjin U, China
  • Yanjun Shi, DLUT, China
  • Dirk Söffker, U Duisburg-Essen, Germany
  • Giuseppe Stecca, CNR, Italy
  • Birgit Vogel-Heuser, TUM, Germany 
  • Chun Wang, Concordia U, Canada
  • Lihui Wang, KTH, Sweden