College of Science and Technology

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    A Systematic Review of the Applications of AI in a Sustainable Building’s Lifecycle
    (Buildings, 2024) Adewale, Bukola; Ene, Vincent Onyedikach; Ogunbayo, Babatunde Fatal; Aigbavboa, Clinton Ohis
    Buildings significantly contribute to global energy consumption and greenhouse gas emis sions. This systematic literature review explores the potential of artificial intelegence (AI) to enhance sustainability throughout a building’s lifecycle. The review identifies AI technologies applicable to sustainable building practices, examines their influence, and analyses implementation challenges. The findings reveal AI’s capabilities in optimising energy efficiency, enabling predictive maintenance, and aiding in design simulation. Advanced machine learning algorithms facilitate data-driven anal ysis, while digital twins provide real-time insights for decision-making. The review also identifies barriers to AI adoption, including cost concerns, data security risks, and implementation challenges. While AI offers innovative solutions for energy optimisation and environmentally conscious practices, addressing technical and practical challenges is crucial for its successful integration in sustainable building practices.
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    Construction 4.0 Application: Industry 4.0, Internet of Things and Lean Construction Tools’ Application in Quality Management System of Residential Building Projects
    (MDPI, Basel, Switzerland., 2022) Amusan, Lekan; Aigbavboa, Clinton; Essien, Stella; Emetere, Moses; Obaju, Biodun
    The advent of Construction 4.0 has played a major role in construction industry develop ment through the improvement of quality performance. One of the parameters that have contributed immensely to the management of construction quality in the industrial revolution era is Industry 4.0, the Internet of Things (IoT), and Lean thinking concepts. Lean construction is characterized by a set of clear objectives in project delivery involving the concurrent design of products and processes. The study aims to carry out an exploratory study of the application of Construction 4.0 and Industrial 4.0 in quality management of building works and the development of Lean-based quality management models: The study engaged a survey design approach, and a random sampling technique was used to select the study samples. A structured questionnaire designed on a Likert scale 1–5 was used to collate data on the quality aspect of a construction project, and the data were used in model creation. The parameters that emerged are cast as the quality management model. The resultant factors were categorized into three (3) quality categories, which are the Zero level Defect range, Medium Quality, and High-Level Quality Range. The three (3) quality factors were recommended for adoption for quality management of residential building projects.