Department of Computer Science & Engineering, BGSB University, Rajouri 185234, Jammu and Kashmir, India.
Department of Electronics & Communication Engineering, BGSB University, Rajouri 185234, Jammu and Kashmir, India.
Sensors (Basel). 2021 Jan 11;21(2):463. doi: 10.3390/s21020463.
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.
确保土壤强度,以及初步的施工成本和工期预测,是任何建筑项目非常关键和初步的方面。同样,在岩土工程中建造坚固的结构对于确保结构对外力的承载能力非常重要。因此,在这个首例的最先进的综述中,探索了各种基于人工智能 (AI) 的模型在准确预测和估算初步施工成本、工期和剪切强度方面的能力。首先,介绍了革命性的 AI 技术及其适用于岩土和施工工程的不同模型的背景。还介绍了文献中关于 AI 模型在施工和维护上述应用中的各种现有工作,以及它们的优点、局限性和未来工作。通过分析,列举并介绍了对估算初步施工成本、工期和土壤剪切强度有重大影响的各种关键输入参数。最后,提出了在这些应用中使用基于 AI 的模型进行准确预测的各种挑战,以及导致成本超支问题的因素。因此,这项研究可以极大地帮助土木工程师有效地利用 AI 的能力来解决复杂和风险敏感的任务,并且它也可以在物联网 (IoT) 环境中用于自动化应用,例如智能结构健康监测系统。