About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
sc 25(1):

Research Article

Integrating Digital Transformation and AI in Civil Engineering: A Multidisciplinary Approach to Disaster Management and Sustainable Urban Development

Download1 download
Cite
BibTeX Plain Text
  • @ARTICLE{10.4108/eetsc.7824,
        author={Dimitrios Sargiotis},
        title={Integrating Digital Transformation and AI in Civil Engineering: A Multidisciplinary Approach to Disaster Management and Sustainable Urban Development},
        journal={EAI Endorsed Transactions on Smart Cities},
        volume={8},
        number={1},
        publisher={EAI},
        journal_a={SC},
        year={2025},
        month={11},
        keywords={Digital Transformation in Civil Engineering, Artificial Intelligence (AI) in Civil Engineering, Machine learning (ML) for Disaster Management, Sustainable and Resilient Urban Development, Virtual and Simulation-Based Engineering Education, Digital Twins and Infrastructure Modeling, AI-Powered Smart City Applications, Internet of Things (IoT) for Environmental Monitoring, Geospatial and Remote Sensing Technologies, Predictive Analytics for Infrastructure Resilience, Ethical and Sustainable AI Integration, Cross-Disciplinary Engineering Innovation, Information and Communication Technology (ICT) for Disaster Risk Reduction},
        doi={10.4108/eetsc.7824}
    }
    
  • Dimitrios Sargiotis
    Year: 2025
    Integrating Digital Transformation and AI in Civil Engineering: A Multidisciplinary Approach to Disaster Management and Sustainable Urban Development
    SC
    EAI
    DOI: 10.4108/eetsc.7824
Dimitrios Sargiotis1,*
  • 1: Εθνικό Μετσόβιο Πολυτεχνείο
*Contact email: dims@central.ntua.gr

Abstract

The rapid advancement of digital technologies, particularly Artificial Intelligence (AI) and Machine Learning (ML), is ushering in a transformative era for civil engineering and disaster management. This paper outlines a multidisciplinary approach that harnesses the power of digital transformation to augment disaster preparedness, response mechanisms, and sustainable urban development. By integrating AI and ML innovations, Information and Communication Technology (ICT) advancements, and emerging technologies like quantum computing and blockchain, this study explores innovative digital solutions aimed at addressing critical challenges within the sector. Key focal points include the application of AI for early prediction and management of natural disasters, the strategic use of ICT in enhancing urban resilience, and the adoption of virtual simulation tools in education to bridge the theoretical-practical gap. Through an in-depth analysis of case studies—ranging from AI-powered mobile applications in smart city ecosystems to advanced materials engineering—this research highlights the potential of digital technologies to build resilient infrastructures, improve public health outcomes, and promote sustainable urban planning. This paper contributes to the ongoing discourse on the role of digital innovation in civil engineering, providing insights into the benefits and challenges of integrating technology into traditional practices, with the ultimate goal of achieving a more sustainable and resilient future.

Keywords
Digital Transformation in Civil Engineering, Artificial Intelligence (AI) in Civil Engineering, Machine learning (ML) for Disaster Management, Sustainable and Resilient Urban Development, Virtual and Simulation-Based Engineering Education, Digital Twins and Infrastructure Modeling, AI-Powered Smart City Applications, Internet of Things (IoT) for Environmental Monitoring, Geospatial and Remote Sensing Technologies, Predictive Analytics for Infrastructure Resilience, Ethical and Sustainable AI Integration, Cross-Disciplinary Engineering Innovation, Information and Communication Technology (ICT) for Disaster Risk Reduction
Received
2024-11-13
Accepted
2025-11-10
Published
2025-11-13
Publisher
EAI
http://dx.doi.org/10.4108/eetsc.7824

Copyright © 2025 Sargiotis Dimitrios, licensed to EAI. This is an open access article distributed under the terms of the CC BY-NCSA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL