Literature DB >> 33440731

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

Sparsh Sharma1, Suhaib Ahmed2, Mohd Naseem1, Waleed S Alnumay3, Saurabh Singh4, Gi Hwan Cho5.   

Abstract

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.

Entities:  

Keywords:  IoT; artificial intelligence; artificial neural network (ANN); construction engineering; geotechnical engineering; pre-parametric cost; project duration; shear strength of soil; support vector machine (SVM)

Year:  2021        PMID: 33440731     DOI: 10.3390/s21020463

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  Internet of Things for Smart Community Solutions.

Authors:  Dhananjay Singh; Mario Divan; Madhusudan Singh
Journal:  Sensors (Basel)       Date:  2022-01-14       Impact factor: 3.576

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.