Abstract

Abstract: At present if we see construction industries, they are facing lot of problems which finally create project delay. The progression of the construction industry is strictly limited by the countless complex challenges it faces such as cost and time overruns, health and safety, productivity and labour scarcities. Working on these complex problems of construction industries is not easy in many aspects but if these problems are countered with the help of AI results will be robust. Therefore, many research efforts in the Architecture, Engineering, and Construction community have recently tried introducing AI into building asset management processes. AI is also able to make the process of decision making faster, decrease error rates, and increase computational efficiency. Among the different AI techniques, machine learning, pattern recognition, and deep learning have recently acquired considerable attention and are establishing themselves as a new class of intelligent methods for use in structural engineering. A present review of existing literature on AI applications in the construction industry such as activity monitoring, risk management, resource and waste optimization was conducted. Additionally, the opportunities and challenges of AI applications in construction were identified and presented in this study. This study focuses on AI and its application in construction industry.

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