Machine learning application in building energy consumption prediction: A comprehensive review DOI

Jingsong Ji,

Hao Yu, Xudong Wang

et al.

Journal of Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 112295 - 112295

Published: March 1, 2025

Language: Английский

An Occupant-centric Control Case Study Based on Internet of Things and Data Mining for an Office Space DOI

Yue Yuan,

Chengcheng Song,

Kejun Zeng

et al.

Journal of Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 111925 - 111925

Published: Jan. 1, 2025

Language: Английский

Citations

0
Sensitivity Analysis of Physical Regularization in Physics-informed Neural Networks (PINNs) of Building Thermal Modeling DOI
Yongbao Chen, Huilong Wang, Zhe Chen

et al.

Building and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 112693 - 112693

Published: Feb. 1, 2025

Language: Английский

Citations

0
The Opportunities and Challenges of Digital Technologies in Energy Systems to Reduce GHG Emissions DOI
Tuğba Dinçbaş,

Aslı Kuzu,

Azize Ergeneli

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Moving Forward in Effective Deployment of the Smart Readiness Indicator and the ISO 52120 Standard to Improve Energy Performance with Building Automation and Control Systems DOI Creative Commons
Gabriela Walczyk, Andrzej Ożadowicz

Energies, Journal Year: 2025, Volume and Issue: 18(5), P. 1241 - 1241

Published: March 3, 2025

The transition towards energy-efficient and sustainable buildings is a cornerstone of global efforts to combat climate change. Building automation control systems (BACSs), standardized under EN ISO 52120, the Smart Readiness Indicator (SRI) have emerged as pivotal tools for optimizing energy performance, integrating smart technologies, enhancing building adaptability. This review provides comprehensive analysis current research landscape practical applications these frameworks, focusing on their role in advancing efficiency, occupant comfort, environmental sustainability. Key contributions include an exploration challenges SRI evaluation, considering limitations simplified methods, need long-term validation, gaps advanced functions. study emphasizes innovative solutions adapting assessments diverse types, conditions, regulatory frameworks. Furthermore, it presents original insights into leveraging including information modeling (BIM) digital twins (DTs), refine evaluation methods optimize BACS designs. These findings contribute development sustainable, intelligent that align with EU goals. authors conclude by highlighting promising directions future further enhance strategic facility management practices.

Language: Английский

Citations

0
Machine learning application in building energy consumption prediction: A comprehensive review DOI

Jingsong Ji,

Hao Yu, Xudong Wang

et al.

Journal of Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 112295 - 112295

Published: March 1, 2025

Language: Английский

Citations

0