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The objective of this research is to develop new algorithms for automated identification of the relevant human perception-attributes of buildings; and enable intelligent and self-tuned comfort delivery systems for customized thermal and visual environments in buildings.
PI: Prof. Karava; Co-PIs: Prof. Bilionis, Prof. Hu
Related projects
Field studies with human subjects to map indoor environment conditions, thermal and visual preferences, occupant-building interactions and corresponding space performance for perimeter building zones
Probabilistic classification of human preference and satisfaction profiles for a typical population
Deep learning-based inference algorithms for online learning of individual and population-level human preferences
Optimal control algorithms and simulation tools for implementation in building management systems
Integration into cyber-enabled technological solutions for self-tuned environments and personal comfort
Related publications
D. Mah, A. Tzempelikos, "Inferring personal daylighting preferences using HDRI and deep learning techniques", Building and Environment, 266, 112128 (2024).
H. Zhang, S. Lee, A. Tzempelikos, “Bayesian Meta-Learning for Personalized Thermal Comfort Modeling”, Building and Environment, 249, 111129 (2024).
H. Zhang, X. Liu, S. Lee, A. Tzempelikos, F. Cappelletti, A. Gasparella, “The impact of personal preference-based thermal control on energy use and thermal comfort: field implementation", Energy and Buildings, 284, 112848 (2023).
H. Zhang, A. Tzempelikos, “Thermal preference-based control studies: Review and detailed classification”, Science and Technology for the Built Environment, 27(8), 1031-1039 (2021).
J. Xiong, N. Awalgaonkar, A. Tzempelikos, I. Bilionis, P. Karava, “Efficient learning of personalized visual preferences in daylit offices: an online elicitation framework”, Building and Environment, 181, 107013 (2020).
S. Lee, P. Karava, A. Tzempelikos, I. Bilionis, “A smart and less intrusive feedback request algorithm towards human-centered HVAC operation”, Building and Environment, 184, 107190 (2020).
S. Lee, J. Joe, P. Karava, I. Bilionis, A. Tzempelikos, “Implementation of a self-tuned HVAC controller to satisfy occupant thermal preferences and optimize energy use”, Energy and Buildings, 194, 301-316 (2019).
J. Xiong, A. Tzempelikos, I. Bilionis, P. Karava, "A personalized daylighting control approach to dynamically optimize visual satisfaction and lighting energy use", Energy and Buildings, 193, 111-126 (2019).
S. Lee, P. Karava, A. Tzempelikos, I. Bilionis, "Inference of thermal preference profiles for personalized thermal environments with actual building occupants", Building and Environment, 148, 714-729 (2019).
J. Xiong, A. Tzempelikos, I. Bilionis, N. Awalgaonkar, S. Lee, I. Konstantzos, A. Sadeghi, P. Karava, “Inferring personalized visual satisfaction profiles in daylit offices from comparative preferences", Building and Environment, 138, 74-88 (2018).
A. Sadeghi, S. Lee, P. Karava, I. Bilionis, A. Tzempelikos, “Bayesian classification and inference of occupant visual preferences in daylit perimeter private offices”, Energy and Buildings, 166, 505-524 (2018).
S. Lee, I. Bilionis, P. Karava, A. Tzempelikos, "A Bayesian approach for probabilistic classification and inference of occupant thermal preferences in office buildings", Building and Environment, 118, 323-343 (2017).
J. Xiong, A. Tzempelikos, “Model-based shading and lighting control considering visual comfort and energy use”, Solar Energy, 134, 416-428 (2016).
A. Sadeghi, P. Karava, I. Konstantzos, A. Tzempelikos, “Occupant interactions with shading and lighting systems using different control interfaces: a pilot field study”, Building and Environment, 97, 177-195 (2016).
P. Karava, A. Tzempelikos, "Predictive controls, modeling and technology assessment for high performance buildings", Editorial, Science and Technology for the Built Environment, 21(6), 719-720 (2015).
H. Zhang, S. Lee, X. Liu, A. Tzempelikos, “Local sensing and personalized thermal comfort: model-predictive vs conventional control approaches”, Proceedings of 6th International High Performance Buildings conference at Purdue, May 2021.
H. Zhang, M. Kim, X. Liu, A. Tzempelikos, “A comparison of sensing type and control complexity techniques for personalized thermal comfort”, Proceedings of ASHRAE Winter Conference, Chicago, January 2021.
S. Lee, J. Joe, P. Karava, I. Bilionis, A. Tzempelikos, "Simulation and implementation of a self-tuned HVAC controller", Proceedings of IBPSA19 Conference, 2079-2085, Rome, Italy, September 2019.
J. Xiong, A. Tzempelikos, P. Karava, I. Bilionis, "Dynamic balancing between personalized daylight preferences and lighting energy use: implementation of a multi-objective optimization framework", Proceedings of IBPSA19 Conference, 1216-1223, Rome, Italy, September 2019.
S. Lee, P. Karava, A. Tzempelikos, I. Bilionis, “Integrating occupants' voluntary thermal preference responses into personalized thermal control in office buildings”, Journal of Physics: Conference series, 1343: 012138. Proceedings of CISBAT2019 Conference, Lausanne, Switzerland, 2019.
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