A Survey on Applications of Artificial Intelligence for Pre-Parametric Project Cost and Soil Shear-Strength Estimation in Construction and Geotechnical Engineering

Sensors

WaleedS. Alnumay¹  Mohd Naseem²  Sparsh Sharma²  Suhaib Ahmed³  Saurabh Singh⁴  GiHwan Cho⁵ 

[1] Computer Science Department, King Saud University, Riyadh 11451, Saudi Arabia;Department of Computer Science & Engineering, BGSB University, Rajouri, Jammu and Kashmir 185234, India;Department of Electronics & Communication Engineering, BGSB University, Rajouri, Jammu and Kashmir 185234, India;Department of Industrial & Systems Engineering, Dongguk University, Seoul 04620, Korea;Division of Computer Science & Engineering, Jeonbuk National University, Jeonju 54896, Korea;

关键词: artificial intelligence;    artificial neural network (ANN);    construction engineering;    geotechnical engineering;    IoT;    pre-parametric cost;   

DOI  :  10.3390/s21020463

来源: DOAJ

【 摘 要 】

Ensuring soil strength, as well as preliminary construction cost and duration prediction, is a very crucial and preliminary aspect of any construction project. Similarly, building strong structures is very important in geotechnical engineering to ensure the bearing capability of structures against external forces. Hence, in this first-of-its-kind state-of-the-art review, the capability of various artificial intelligence (AI)-based models toward accurate prediction and estimation of preliminary construction cost, duration, and shear strength is explored. Initially, background regarding the revolutionary AI technology along with its different models suited for geotechnical and construction engineering is presented. Various existing works in the literature on the usage of AI-based models for the abovementioned applications of construction and maintenance are presented along with their advantages, limitations, and future work. Through analysis, various crucial input parameters with great impact on the estimation of preliminary construction cost, duration, and soil shear strength are enumerated and presented. Lastly, various challenges in using AI-based models for accurate predictions in these applications, as well as factors contributing to the cost-overrun issues, are presented. This study can, thus, greatly assist civil engineers in efficiently using the capabilities of AI for solving complex and risk-sensitive tasks, and it can also be used in Internet of things (IoT) environments for automated applications such as smart structural health-monitoring systems.

【 授权许可】

Unknown