Application of artificial intelligence in the Nigerian building and construction industry

被引:0
|
作者
Owolabi, James Dele [1 ]
Malagwi, Dzarma [1 ]
Oyeyipo, Opeyemi [2 ]
Ola-Ade, Esther Oluwafolakemi [3 ]
Tunji-Olayeni, Patience Fikiemo [1 ]
机构
[1] Covenant Univ, Dept Bldg Technol, Ota, Nigeria
[2] Bells Univ Technol, Dept Quant Surveying, Ota, Nigeria
[3] Univ Lagos, Dept Quant Surveying, Lagos, Nigeria
关键词
4th industrial revolution; Construction automation; Industry; 4.0; Project performance; Smart construction;
D O I
10.21833/ijaas.2022.10.005
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The uniqueness and inherent complexities of the construction industry require the use of Artificial Intelligence (AI) to improve its processes and enhance overall competitiveness and performance. This study examined the awareness level and application of AI to provide useful insights into the state of AI applications in the Nigerian construction industry. A quantitative research design with the use of a questionnaire was used to obtain data from 53 construction professionals in the Lagos Island area of Lagos State, Nigeria. The professionals included Quantity Surveyors, Architects, Civil Engineers, Builders, and Estate Surveyors selected based on a purposive sampling technique. Data from the survey were analyzed with frequencies, mean, and ANOVA. The study found that most of the respondents were aware of the application of AI in construction, and there was no difference in the awareness level of the participants irrespective of their professional affiliations, organizational type, and organizational size. Generally, the most common application of AI among the participants surveyed were generative designs in BIM, measurement and estimating software, and the use of sensors in intelligent buildings. Moreover, design and project planning was found to be the most critical areas of need for AI in the study area. The study underscores the need for investments in other AI applications other than BIM and estimating software to improve productivity, performance, and enhance client satisfaction. (C) 2022 The Authors. Published by IASE.
引用
收藏
页码:33 / 39
页数:7
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