Human-Centric Based Energy and Comfort Optimization in Cognitive Buildings: A Review - Khan, Irfanullah; Guerrieri, Antonio; Cicirelli, Franco; McGough, A. Stephen; Spezzano, Giandomenico (2024 IEEE Conference on Pervasive and Intelligent Computing (PICom), 2024)
A Cognitive Building (CB) is a cutting-edge environment that automatically adjusts its settings based on insights gained through continuous learning. These buildings employ adaptive strategies to improve security, energy efficiency, and comfort by analyzing occupant behavior, adhering to user requirements, and complying with user-defined rules. This adaptation begins with understanding how occupants use the space, including when, how, and where they occupy it. By utilizing data from different smart objects, CBs can effectively monitor and forecast user behavior, providing proactive options to enhance their experience. This paper provides a review of the most recent progress in using occupant behaviors to empower CBs to make autonomous choices, thereby enhancing security, energy efficiency, and comfort. As a novelty, it investigates how detailed information on building occupancy, including if the building is occupied, the number of people, their activity, and their precise positions within the space, could improve and optimize decision-making procedures. Furthermore, it also explores the challenges associated with the implementation of these concepts and discusses the potential future research directions that could enhance these concepts.