International Journal of Artificial Intelligence and Machine Learning
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Volume 3, Issue 2, July 2023 | |
Research PaperOpenAccess | |
Optimizing Construction Productivity Through Automation and Artificial Intelligence |
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1Department of Electrical and Electronics Engineering, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg 2006, South Africa. E-mail: 220117941@student.uj.ac.za
*Corresponding Author | |
Int.Artif.Intell.&Mach.Learn. 3(2) (2023) 28-44, DOI: https://doi.org/10.51483/IJAIML.3.2.2023.28-44 | |
Received: 16/02/2023|Accepted: 21/06/2023|Published: 05/07/2023 |
This paper examines the potential of automation and Artificial Intelligence (AI) to enhance construction productivity. Automation and AI can be used to increase the productivity of the construction industry by reducing labor costs, boosting productivity, and enhancing safety. Automation and AI can also be used to increase the precision of project estimates, decrease the time required to complete projects and decrease the amount of manual labor required. Beginning with a discussion of the present state of construction productivity, the paper identifies the obstacles that must be overcome to optimize it. The section then investigates the potential of automation and AI to increase construction productivity. It examines how automation and AI can be utilized to reduce labor costs, enhance safety, and boost precision. The paper also examines the potential for AI to improve project estimations, reduce project completion times, and reduce the amount of manual labor required. Additionally, the research investigates the difficulties and dangers associated with automation and AI in the construction industry. These include the possibility of an increase in errors, the danger of over-automation, and the need for personnel to be properly trained. The paper then describes the steps that can be taken to maximize the benefits of automation and AI while minimizing the associated risks.
Keywords: Artificial intelligence, Construction productivity, Automated construction, Automation technology
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