IoT-Enabled Data-Driven Collaborative Intelligent Systems

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Internet of Things (IoT) has been widely accepted as a novel paradigm that can radically transform industry and 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 is a broad term for data sets so large or complex that traditional data processing technologies are inadequate. It has recently been considered as a technology and become a very active research area primarily involving topics related to machine learning, database, and distributed computing. It has been claimed that “the success or failure of the Internet of Things hinges on Big Data”. IoT and Big Data bring great opportunities to improve agent-based collaborative intelligent systems that have been proposed, developed, and deployed during the past twenty-five years. However, these new technologies also bring significant challenges and do not address major issues such as system reliability, security, efficiency, and trust management. Significant R&D efforts are required before these technologies can be widely deployed in industrial applications. The long-term goal of this research program is to develop scientific and engineering foundations, innovative technologies and solutions for IoT-enabled data-driven collaborative intelligent systems, with particular attention to the application domain of intelligent buildings. At the fundamental research level, the focus will be on the development an IoT-enabled data-driven platform for integrating Cloud Computing, IoT, Big Data, agent, and blockchain technologies for collaborative intelligent systems. The resulting platform and related technologies will be generic enough for applications to different industrial domains, including intelligent buildings, smart homes, smart factories, and smart cities. In the intelligent building application domain, the focus will be on the development of Big Data analytic techniques and solutions for automated fault detection, diagnostics and failure prediction. Finally, all the resulting technologies and solutions will be validated and demonstrated through pilot implementations. This research will result in substantial advancements in understanding, modelling, designing, and implementing IoT-enabled data-driven collaborative intelligent systems. The resulting technologies will have a world-wide clientele and will put Canadian industries and universities in forefront of innovation, and help Canada emerge as a global technology leader. The proposed research program will also offer a great HQP training opportunity and provide Canadian industries with potential experts in collaborative intelligent systems and intelligent buildings, a profession believed to be in high demand in the next five to ten years.