Artificial intelligence in the construction industry / Nurul Najihah Mad Rosni

Mad Rosni, Nurul Najihah (2023) Artificial intelligence in the construction industry / Nurul Najihah Mad Rosni. RISE: Catalysing Global Research Excellence (3): 14. pp. 1-4. ISSN 2805-5883


The ‘old’ construction industry has obvious issues in terms of labour shortage, waste of manpower, delays, and inefficiency in planning, forecasting and budgeting. Numerous studies have revealed that unsafe working conditions and lack of monitoring relates to concerns on safety, drawing attention to the need for management in the construction industry to ensure safety and to prevent accidents. Due to the remarkable growth of artificial intelligence (AI) technology and its application in the construction industry, it has been proven that AI based approaches have the ability to assist in addressing significant weaknesses of traditional construction management that rely on manual observation and operational, which are more susceptible to bias and rather confusing. Building and construction industry continuously develop new technologies that drives economic growth linked to intensification of the productivity, quality and safety of the project. Artificial intelligence (AI) is a subfield of computer science that enables machine to perceive and develop human-like inputs for perception, knowledge representation, reasoning, planning and problem solving, so they may cope with complex and fuzzy issues in a deliberate, intelligent and adaptive way. There are numerous applications of AI in analysis, loading capacity prediction, and damage level prediction of existing structures for retrofitting. AI algorithms and models could function to enhance the analysis of buckling and fatigue of structural components. In fact, AI could also be used to improve the loading capacity and improve damage level prediction in existing structures for retrofitting.


Item Type: Article
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Mad Rosni, Nurul Najihah
Subjects: H Social Sciences > HD Industries. Land use. Labor > Construction industry
Q Science > Q Science (General) > Back propagation (Artificial intelligence)
Divisions: Universiti Teknologi MARA, Shah Alam > Vice Chancellor Office > Pejabat Timbalan Naib Canselor (Penyelidikan & Inovasi)
Journal or Publication Title: RISE: Catalysing Global Research Excellence
ISSN: 2805-5883
Number: 3
Page Range: pp. 1-4
Keywords: Old construction, architectural layouts, structural design
Date: November 2023
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