Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India

Research Article

Unveiling the Future of Engineering Management: The Role of Artificial Intelligence and Big Data

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  • @INPROCEEDINGS{10.4108/eai.17-11-2023.2342763,
        author={Hongye  Cui and Chuan  Xu and Kangjie  Sun},
        title={Unveiling the Future of Engineering Management: The Role of Artificial Intelligence and Big Data},
        proceedings={Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India},
        publisher={EAI},
        proceedings_a={ICSETPSD},
        year={2024},
        month={1},
        keywords={artificial intelligence big data engineering management project planning risk management resource optimization progress control},
        doi={10.4108/eai.17-11-2023.2342763}
    }
    
  • Hongye Cui
    Chuan Xu
    Kangjie Sun
    Year: 2024
    Unveiling the Future of Engineering Management: The Role of Artificial Intelligence and Big Data
    ICSETPSD
    EAI
    DOI: 10.4108/eai.17-11-2023.2342763
Hongye Cui1, Chuan Xu1, Kangjie Sun1,*
  • 1: School of Civil Engineering, Hebei University of Science and Technology, Shijiazhuang, Hebei, China
*Contact email: sunkj0606@126.com

Abstract

This paper explores the transformative role of Artificial Intelligence (AI) and Big Data in the field of Engineering Management. With the rising complexity of projects, traditional management methodologies are increasingly challenged to keep up. However, recent technological advancements in AI and Big Data offer promising solutions to these challenges. This study examines how AI and Big Data can be effectively integrated into engineering management, specifically focusing on project planning, progress tracking, risk identification and management, as well as resource optimization and scheduling. Through a comprehensive review of existing literature and detailed case studies, we highlight how these technologies can enhance decision-making processes; improve prediction accuracy, and ultimately lead to more efficient and successful project outcomes. In particular, AI's potential to automate and optimize project planning and risk management is assessed, along with Big Data's ability to enhance resource allocation and progress control through advanced predictive analytics. The findings of this research underline the significant potential of AI and Big Data to revolutionize the field of engineering management, providing practical insights for both practitioners and academics alike.