Integrating BIM and AI For Smart Energy Systems: A Lean Construction Approach to Developing Sustainable and Resilient Infrastructure Cover Image

Integrating BIM and AI For Smart Energy Systems: A Lean Construction Approach to Developing Sustainable and Resilient Infrastructure
Integrating BIM and AI For Smart Energy Systems: A Lean Construction Approach to Developing Sustainable and Resilient Infrastructure

Author(s): Olamide Segun Olatunji, Adebayo Okegbemi, Stanley Abela Udoh, Alawode Deborah Oluwabusola, Ademola Peter Alademomi, Anaebo Johnpaul Chukwuka
Subject(s): Architecture, Business Economy / Management, Energy and Environmental Studies, Management and complex organizations, Policy, planning, forecast and speculation, ICT Information and Communications Technologies
Published by: Altezoro, s. r. o. & Dialog
Keywords: Building Information Modelling; Artificial Intelligence; Lean Construction; Smart Energy Systems; Sustainable Infrastructure; Digital Twins;

Summary/Abstract: The construction industry faces unprecedented challenges in fulfilling its role in building sustainable, resilient infrastructure while managing growing complexity and resource constraints. This article discusses how the Building Information Model (BIM), artificial intelligence (AI), and Lean Construction principles are synergistically integrated to optimise innovative energy systems in a building environment. Through a wide-ranging review of the latest literature and case studies, this paper shows how, with the confluence of these technologies, predictive energy management, waste reduction, and better decision-making can be achieved across the project lifecycle. The results show that integrated BIM-AI frameworks can save 20-35% in energy use, reduce construction waste by up to 30%, and deliver projects 25-40% more efficiently. This research adds to the growing body of knowledge on digital transformation in construction, offering valuable insights for industry practitioners seeking to implement sustainable solutions in the infrastructure sector.

  • Issue Year: 11/2025
  • Issue No: 12
  • Page Range: 4030-4039
  • Page Count: 10
  • Language: English
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