JOURNAL ARTICLE

The sustainable smart security construction site management using fuzzy evaluation and artificial intelligence.

  • Published In: Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.), 2025, v. 25, n. 1. P. 160 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Song, Lei 3 of 3

Abstract

The article focuses on managing Smart Construction Sites (SCSs) and reducing associated risks through Artificial Intelligence (AI), proposing a sustainable SCS management system. This system integrates the Fuzzy Comprehensive Evaluation (FCE) method, biometric identification technology, and Building Information Modeling (BIM) to enhance safety training, real-time monitoring, and resource utilization. Experimental results indicate that the system significantly reduces annual risks from 36,700 to 3,500, improves material resource utilization by 20%, and lowers construction costs. The study highlights the system’s potential to support government and business decision-making, promote sustainable construction practices, and contribute to the growth of China’s construction industry, while acknowledging limitations related to research scale and the need for further validation. Future research directions include applying blockchain technology to improve risk response, environmental monitoring, and system maintenance within SCS management.

Additional Information

  • Source:Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.). 2025/01, Vol. 25, Issue 1, p160
  • Document Type:Article
  • Subject Area:Construction and Building
  • Publication Date:2025
  • ISSN:1472-7978
  • DOI:10.1177/14727978241299235
  • Accession Number:184747308
  • Copyright Statement:Copyright of Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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