AI vs. human mind: efficiency in the management of construction industry

Ang Soon Ern, Peniel and Jong, Oi Ka and Safea’ai, Muhammad Aqerul and Mohd Saip, Muhammad Amirul Rasyid and Mohamed Salehin, Nur Ili Izyan (2022) AI vs. human mind: efficiency in the management of construction industry. In: Multidisciplinary Engineering Science and Advanced Technology. Penerbit UTHM, UTHM, pp. 34-40. ISBN 978-967-2817-40-6

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Abstract

The digitalisation of construction industry is driving to embrace smart construction with emerging technologies for its productiveness. Artificial Intelligent (AI) is one of the cutting-edge technologies that demonstrates efficiency and effectiveness in construction project lifecycle. For instance, prevent cost overrun, create generative design with Building Information Modelling (BIM), conduct logistics management in site, and perform periodic facility management. Despite the significant implications of AI in construction value chain, there are disagreements among the community on the effectiveness of AI implementation in construction industry. Hence, this study compares the efficiency of both AI and human mind in the management of construction industry. The result presented that AI play an important role to assist human in resolving high volume of data effectively, store massive data securely at a place and unlimited usage to complete repetitive work. This study breaks the perception of public where AI implementation could replace human mind or it is a cumbersome process to adopt. The characteristic of AI should be utilised to improve the efficiency and productivity of construction management.

Item Type:	Book Section
Uncontrolled Keywords:	Artificial Intelligent (AI); human mind; Industry Revolution 4.0 (IR 4.0); management construction
Subjects:	T Technology > TH Building construction
Divisions:	Faculty of Engineering Technology > Department of Civil Engineering Technology
Depositing User:	Mr. Abdul Rahim Mat Radzuan
Date Deposited:	22 Mar 2022 03:27
Last Modified:	22 Mar 2022 03:27
URI:	http://eprints.uthm.edu.my/id/eprint/6830

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