Functional analysis of LIDAR technology in optimizing efficiency and sustainability in construction sector DOI Creative Commons
Ahsan Waqar, Dorin Radu, Badr T. Alsulami

et al.

Ain Shams Engineering Journal, Journal Year: 2024, Volume and Issue: 16(2), P. 103258 - 103258

Published: Dec. 31, 2024

Language: Английский

Active learning-based machine learning approach for enhancing environmental sustainability in green building energy consumption DOI Creative Commons
Shahid Mahmood,

Huaping Sun,

Amel Ali Alhussan

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 27, 2024

Abstract Green building (GB) techniques are essential for reducing energy waste in the construction sector, which accounts almost 40% of global consumption. Despite their importance, challenges such as occupant behavior and management gaps often result GBs consuming up to 2.5 times more than intended. To address this, Building Automation Systems (BAS) play a crucial role enhancing efficiency. This research develops predictive model GB design using machine learning minimize consumption improve indoor sustainability. The dataset is utilized predict cooling heating individually, with data visualization by graphically illustrating features preprocessing through Z-Score normalization splitting. proposed model, based on active utilizing ML regressors Random Forest (RF), Decision Tree (DT), Gradient Boosting (GB), Extreme (XGBoost), CatBoost (CB), Light Machine (LGBM), K-Nearest Neighbor (KNN), Logistic Regressor (LR), shows significant performance improvements. CBR-AL achieves impressive results values 0.9975 (Y1) 0.9883 (Y2), indicating high level accuracy. model’s success improving sustainability has potential ripple effects, including substantial cost savings, reduced carbon footprints, improved operational efficiency green buildings. approach not only enhances environmental but also sets benchmark future advancements modelling management.

Language: Английский

Citations

6
Leveraging BIM for Sustainable Construction: Benefits, Barriers, and Best Practices DOI Open Access

Qiuli Cheng,

Bassam A. Tayeh, Yazan I. Abu Aisheh

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7654 - 7654

Published: Sept. 3, 2024

The building sector is still criticized for its excessive energy use and negative environmental effects, even with significant improvements in recent years. It makes a major contribution to the world’s energy, waste, water use. This study investigates possible benefits of using Building Information Modeling (BIM) technology environmentally friendly methods. also seeks identify rank obstacles industry’s integration sustainability BIM. aims accomplish research objectives by means questionnaire survey approach. three primary categories associated BIM are social, economic, environmental, which correspond generally acknowledged elements sustainable development. provision centralized database that facilitates administration full lifetime, less material increased design efficiency have all been noted as key benefits. In industry, approaches shown be quite successful improving practices. does, however, point out few difficulties. number people degree has significantly, but there not enough qualified professionals necessary knowledge experience. Project managers skills needed oversee deployment successfully. They should able advice counsel clients other stakeholders on may maximize performance structures across their lifetimes make well-informed decisions integrating concepts into process.

Language: Английский

Citations

5
AI-Driven Design Optimization for Sustainable Buildings: A Systematic Review DOI Creative Commons

Piragash Manmatharasan,

Girma Bitsuamlak, Katarina Grolinger

et al.

Energy and Buildings, Journal Year: 2025, Volume and Issue: unknown, P. 115440 - 115440

Published: Feb. 1, 2025

Language: Английский

Citations

0
Optimizing sustainable alternatives in value engineering Decision-Making through BIM-Integrated plugin automation for buildings DOI

Abdul Mateen Khan,

Wesam Salah Alaloul, Muhammad Ali Musarat

et al.

Ain Shams Engineering Journal, Journal Year: 2025, Volume and Issue: 16(6), P. 103373 - 103373

Published: April 1, 2025

Language: Английский

Citations

0
Key factors shaping post-disaster building damage assessment: insights from the Gaza Strip as a conflict zone DOI Creative Commons

Sahar Salah El Ghoul,

Bassam A. Tayeh, Ahmad Baghdadi

et al.

Journal of Asian Architecture and Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 21

Published: April 1, 2025

Language: Английский

Citations

0
Sustainability in construction economics as a barrier to cloud computing adoption in small-scale Building projects DOI Creative Commons
Zonghui Wang,

Kalugina Olga Veniaminovna,

Volichenko Olga Vladimirovna

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 2, 2025

Language: Английский

Citations

0
AI-Enhanced Automation of Building Energy Optimization Using a Hybrid Stacked Model and Genetic Algorithms: Experiments with Seven Machine Learning Techniques and a Deep Neural Network DOI Creative Commons
Mohammad H. Mehraban, Samad M. E. Sepasgozar,

Alireza Ghomimoghadam

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104994 - 104994

Published: April 1, 2025

Language: Английский

Citations

0
Unveiling Drivers of Zone-Specific Air Quality Predictions Using Explainable Ai: Shapley Additive Explanations-Based Insights Across Formal and Informal End-of-Life Vehicle Recycling Zones with a Green Zone Benchmark DOI
Altaf Hossain Molla, Zambri Harun,

Demiral Akbar

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Optimizing Energy Efficiency Through Building Orientation and Building Information Modelling (BIM) in Diverse Terrains: A Case Study in Pakistan DOI

Abdul Mateen Khan,

Muhammad Abubakar Tariq,

Zeshan Alam

et al.

Energy, Journal Year: 2024, Volume and Issue: unknown, P. 133307 - 133307

Published: Oct. 1, 2024

Language: Английский

Citations

3
The Relationship Between Artificial Intelligence (AI) and Building Information Modeling (BIM) Technologies for Sustainable Building in the Context of Smart Cities DOI Open Access
Jinyi Li, Zhen Liu,

Guizhong Han

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(24), P. 10848 - 10848

Published: Dec. 11, 2024

The development of information technologies has been exponentially applied to the architecture, engineering, and construction (AEC) industries. extent literature reveals that two most pertinent are building modeling (BIM) artificial intelligence (AI) technologies. radical digitization AEC industry, enabled by BIM AI, contributed emergence “smart cities”, which uses technology improve urban operational sustainable efficiency. Few studies have investigated roles AI in from perspective buildings assisting designers make decisions at city levels. Therefore, purpose this paper is explore research status future trends relationship between BIM-aided context smart provide researchers, designers, developers with potential directions. This adopted a macro micro bibliographic method, used map out general landscape. followed more in-depth analysis fields design, construction, development, life cycle assessment (LCA). results show combination helps optimal on materials, cost, energy, scheduling, monitoring promotes both technical human aspects so achieve Sustainable Development Goals 7 (ensuring access affordable, reliable, modern energy for all), 9 (building resilient infrastructure, promote inclusive industries, foster innovation), 11 inclusive, safe, risk-resilient, cities settlements), 12 consumption production patterns). In addition, BIM, LCA offers great performance, integration should not only consider sustainability but also human-centered design concept health, safety, comfort stakeholders as one goals realize multidimensional based model.

Language: Английский

Citations

3