Markov Chain-based Algorithms for Building Occupancy Modeling: A Review

septembre 2021
Ingénierie & Outils numériques
Communications avec actes dans un congrès international
Auteurs : Chinmayi Kanthila (LINEACT & IRDL), Abhinandana Boodi (LINEACT), Karim Beddiar (LINEACT), Yassine Amirat (L@bISEN), Mohamed Benbouzid (UMR CNRS 6027 IRDL)
Conférence : 2021 3rd International Conference on Smart Power & Internet Energy Systems, 24 septembre 2021

Smart buildings focus on providing optimal comfort for the occupant with reduced energy consumption. Better occupant prediction and behavior analysis can significantly reduce building energy usage. Human being is an important parameter in the building control process and his comfort is paramount. Therefore, occupant modeling is critical in improving building efficiency while maintaining indoor comfort. Although, there are many different algorithms developed for occupancy modeling, the Markov chain, and its derivative models are extensively used because of their simplicity, flexibility, and prediction efficiency. In this context, this paper proposes a state-of-the-art review focused on the Markov chain and its derivative models for occupant modeling.