Special Issue

AI-Driven Digital Engineering and Intelligent Solutions for Energy Performance and Sustainability in the Built Environment

Submission Deadline: August 31, 2027 (Open) Submit Now

Guest Editor

Ali Bahadori-Jahromi, PhD, Professor

Department of Civil Engineering and Built Environment, School of Computing and Engineering, University of West London, London W5 5RF, UK

Website1 | Website2 | E-Mail

Research Interests: sustainable construction, low-carbon materials, building energy performance, climate resilience, and AI-driven digital engineering solutions.

About This Topic

This Special Issue aims to present recent advances in the application of artificial intelligence, machine learning, and digital engineering to improve the energy performance, sustainability, and resilience of the built environment. Original research, review papers, and practical case studies are invited on topics including digital twins, Building Information Modelling (BIM), intelligent building energy management, IoT-enabled monitoring, predictive maintenance, optimisation techniques, computer vision, renewable energy integration, climate-responsive design, and smart cities. Contributions on energy-efficient concrete and construction materials, embodied carbon assessment, life-cycle analysis, retrofit strategies, HVAC optimisation, and AI-assisted decision-making for buildings and civil infrastructure are also encouraged. The Special Issue seeks to promote innovative, evidence-based digital solutions that support the transition towards low-carbon, energy-efficient, and resilient buildings and infrastructure.

Keywords

Artificial Intelligence; Machine Learning; Digital Engineering; Building Information Modelling (BIM); Digital Twins; Building Energy Performance; Smart Buildings; Internet of Things (IoT); Energy Efficiency; Sustainable Construction; Energy-Efficient Concrete; Renewable Energy; Climate-Responsive Design; Life-Cycle Assessment; Embodied Carbon; Predictive Maintenance; Smart Cities; Net-Zero Carbon; Built Environment

Manuscript Submission Information

Manuscripts should be submitted through the LIDSEN Submission System. Detailed information on manuscript preparation and submission is available in the Instructions for Authors. All submitted articles will be thoroughly refereed through a single-blind peer-review process and will be processed following the Editorial Process and Quality Control policy. Upon acceptance, the article will be immediately published in a regular issue of the journal and will be listed together on the special issue website, with a label that the article belongs to the Special Issue. LIDSEN distributes articles under the Creative Commons Attribution (CC BY 4.0) License in an open-access model. The authors own the copyright to the article, and the article can be free to access, distribute, and reuse provided that the original work is correctly cited.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). Research articles and review articles are highly invited. Authors are encouraged to send the tentative title and abstract of the planned paper to the Editorial Office (aeer@lidsen.com) for record. If you have any questions, please do not hesitate to contact the Editorial Office.

Welcome your submission!