Advanced controls on energy reliability, flexibility, resilience, and occupant-centric control for smart and energy-efficient buildings—a state-of-the-art review

Z Liu, X Zhang, Y Sun, Y Zhou - Energy and Buildings, 2023 - Elsevier
Advanced controls have attracted increasing interests due to the high requirement on smart
and energy-efficient (SEE) buildings and decarbonization in the building industry with …

[HTML][HTML] A critical review of occupant energy consumption behavior in buildings: How we got here, where we are, and where we are headed

X Xu, H Yu, Q Sun, VWY Tam - Renewable and Sustainable Energy …, 2023 - Elsevier
Occupant behavior has been widely considered as one of the key influencing factors on
building energy consumption. The complexity of its formation mechanism and the dynamic …

A practical deep reinforcement learning framework for multivariate occupant-centric control in buildings

Y Lei, S Zhan, E Ono, Y Peng, Z Zhang, T Hasama… - Applied Energy, 2022 - Elsevier
Reinforcement learning (RL) has been shown to have the potential for optimal control of
heating, ventilation, and air conditioning (HVAC) systems. Although research on RL-based …

[HTML][HTML] Energy, thermal comfort, and indoor air quality: Multi-objective optimization review

T Al Mindeel, E Spentzou, M Eftekhari - Renewable and Sustainable …, 2024 - Elsevier
The reliance on optimization techniques for robust assessments of environmental and
energy-saving solutions has been largely driven by the increasing need to comply with …

[HTML][HTML] From time-series to 2d images for building occupancy prediction using deep transfer learning

AN Sayed, Y Himeur, F Bensaali - Engineering Applications of Artificial …, 2023 - Elsevier
Building occupancy information could aid energy preservation while simultaneously
maintaining the end-user comfort level. Energy conservation becomes essential since …

Learning-Based personal models for joint optimization of thermal comfort and energy consumption in flexible workplaces

M Deng, B Fu, CC Menassa, VR Kamat - Energy and Buildings, 2023 - Elsevier
Due to distinct preferences across individuals, a large proportion of people are not satisfied
with the thermal environments of their workplaces. Although recent studies have …

Comparison of models for predicting winter individual thermal comfort based on machine learning algorithms

B Yang, X Li, Y Liu, L Chen, R Guo, F Wang… - Building and …, 2022 - Elsevier
Abstract Machine learning-based human thermal comfort prediction is becoming
increasingly popular as artificial intelligence (AI) technologies advance. Human skin …

Human-building interaction for indoor environmental control: Evolution of technology and future prospects

H Kim, H Kang, H Choi, D Jung, T Hong - Automation in Construction, 2023 - Elsevier
This paper presents a data-driven literature review of human-building interaction (HBI),
which refers to the interaction between occupants and buildings. Through natural language …

Blockchain-based IoT system for personalized indoor temperature control

J Jeoung, S Jung, T Hong, JK Choi - Automation in Construction, 2022 - Elsevier
This study aimed to develop a blockchain-based IoT (BIoT) system for adopting automated
personalized indoor temperature control to the building management system (BMS) while …

Performance evaluation of personal thermal comfort models for older people based on skin temperature, health perception, behavioural and environmental variables

LA Martins, V Soebarto, T Williamson - Journal of Building Engineering, 2022 - Elsevier
Personal thermal comfort models hold the promise of a more accurate way to predict thermal
comfort and therefore a more reliable approach for managing indoor thermal environments …