Data-driven prediction and optimization toward net-zero and positive-energy buildings: A systematic review
SN Mousavi, MG Villarreal-Marroquín… - Building and …, 2023 - Elsevier
Recent advances toward sustainable cities have promoted the concept of near-zero energy
consumption. A Positive Energy Building (PEB) model has been developed by the European …
consumption. A Positive Energy Building (PEB) model has been developed by the European …
[HTML][HTML] Next-generation energy systems for sustainable smart cities: Roles of transfer learning
Smart cities attempt to reach net-zero emissions goals by reducing wasted energy while
improving grid stability and meeting service demand. This is possible by adopting next …
improving grid stability and meeting service demand. This is possible by adopting next …
[HTML][HTML] From time-series to 2d images for building occupancy prediction using deep transfer learning
Building occupancy information could aid energy preservation while simultaneously
maintaining the end-user comfort level. Energy conservation becomes essential since …
maintaining the end-user comfort level. Energy conservation becomes essential since …
Combining physical approaches with deep learning techniques for urban building energy modeling: A comprehensive review and future research prospects
In recent times, there has been a growing interest in urban building energy modeling
(UBEM), owing to its potential benefits for cities. These benefits include aiding city decision …
(UBEM), owing to its potential benefits for cities. These benefits include aiding city decision …
Unsupervised domain adaptation with and without access to source data for estimating occupancy and recognizing activities in smart buildings
Energy-efficient buildings have gained increasing interest in the last decades as they
provide optimal energy management. With the emergence of smart homes, many smart tools …
provide optimal energy management. With the emergence of smart homes, many smart tools …
The use of GANs and transfer learning in model-order reduction of turbulent wake of an isolated high-rise building
The high cost of computational fluid dynamics (CFD) simulations has limited their use for
real-time and long-term simulations. To address this limitation, reduced-order modeling has …
real-time and long-term simulations. To address this limitation, reduced-order modeling has …
Unsupervised domain adaptation without source data for estimating occupancy and recognizing activities in smart buildings
Abstract Activities Recognition (AR) and Occupancy Estimation (OE) are topics of current
interest. AR and OE help many smart building applications such as energy systems and …
interest. AR and OE help many smart building applications such as energy systems and …
[HTML][HTML] Deep learning models for vision-based occupancy detection in high occupancy buildings
Accurate occupancy information is crucial for enhancing energy efficiency and reducing
carbon emissions in buildings. However, the inherent unpredictability of occupants …
carbon emissions in buildings. However, the inherent unpredictability of occupants …
Transfer learning for occupancy-based HVAC control: A data-driven approach using unsupervised learning of occupancy profiles and deep reinforcement learning
M Esrafilian-Najafabadi, F Haghighat - Energy and Buildings, 2023 - Elsevier
Abstract Model-free heating, ventilation, and air conditioning (HVAC) control systems have
demonstrated promising potential for adjusting indoor setpoint temperature based on …
demonstrated promising potential for adjusting indoor setpoint temperature based on …
Transfer learning in human activity recognition: A survey
SG Dhekane, T Ploetz - arXiv preprint arXiv:2401.10185, 2024 - arxiv.org
Sensor-based human activity recognition (HAR) has been an active research area, owing to
its applications in smart environments, assisted living, fitness, healthcare, etc. Recently …
its applications in smart environments, assisted living, fitness, healthcare, etc. Recently …