A Risk Identification and Early Warning System for Major Engineering Projects Based on Artificial Intelligence
Download as PDF
DOI: 10.25236/icmmct.2024.034
Author(s)
Zhenyao Yin, Xing Ren
Corresponding Author
Xing Ren
Abstract
Artificial intelligence (AI), as a hot topic in today's technology field, has shown enormous potential for widespread application in various fields. In the management of major engineering projects, its efficient and precise characteristics are particularly prominent. Traditional identification and early warning methods often have problems such as low efficiency and easy omission in identifying potential risk factors in major engineering projects. Therefore, risk identification and automatic warning systems based on AI technology have emerged, providing strong guarantees for the smooth progress of engineering projects. This system achieves real-time monitoring and analysis of various data in engineering projects through advanced technologies such as machine learning (ML) and big data analysis. By comprehensively processing multidimensional information such as environmental data, equipment status data, and personnel activity data, the system can automatically identify potential risk factors and provide real-time warnings based on preset rules and algorithms. This warning mechanism not only improves the accuracy of risk identification, but also greatly shortens the response time of warnings, providing valuable decision-making basis for project management personnel.
Keywords
Artificial Intelligence; Major engineering projects; Risk identification; early warning system