Implementation of Artificial Intelligence in the Construction Industry and Analysis of Existing Technologies
Technology Audit and Production Reserves, 2(2(58), 12–15 (2021). doi: 10.15587/2706-5448.2021.229532
4 Pages Posted: 20 May 2021
Date Written: April 30, 2021
The object of research is the process of using information technology in the construction industry. One of the most problematic areas is increasing the efficiency of the construction industry through the introduction of digital technologies. The research carried out is based on the application of an approach that is implemented using artificial intelligence. The study used machine learning and fuzzy logic methods to mark visual data and analyze it for potential threats, as well as to reduce all possible risks. The main feature of this approach is that using machine learning technology, it is possible to reduce the risks of a project before they affect its profit. So, using artificial intelligence in combination with BIM technologies, it is possible to predict work on construction projects based on real-time data, past activities and other factors in such a way as to optimize construction processes. The benefits to be gained from implementing digital processes will become even more evident in future projects as AI continues to analyze company data. This is due to the fact that the proposed approach using fuzzy logic has a number of features, in particular, the more information machine learning algorithms process, the more complex they become. As a result, they provide even more useful information and allow to make even better decisions. This provides an opportunity to minimize risks and efficiently allocate resources when working on projects. Compared to conventional information technology, artificial intelligence can be used to build a knowledge-based security management system and combine statistical probabilities to help mitigate security risks in construction projects.
Keywords: artificial intelligence, information technology, BIM technology, machine learning, automation of the construction industry
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