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Disaster City Digital Twin: A vision for integrating artificial and human intelligence for disaster management

Author

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  • Fan, Chao
  • Zhang, Cheng
  • Yahja, Alex
  • Mostafavi, Ali

Abstract

This paper presents a vision for a Disaster City Digital Twin paradigm that can: (i) enable interdisciplinary convergence in the field of crisis informatics and information and communication technology (ICT) in disaster management; (ii) integrate artificial intelligence (AI) algorithms and approaches to improve situation assessment, decision making, and coordination among various stakeholders; and (iii) enable increased visibility into network dynamics of complex disaster management and humanitarian actions. The number of humanitarian relief actions is growing due to the increased frequency of natural and man-made crises. Various streams of research across different disciplines have focused on ICT and AI solutions for enhancing disaster management processes. However, most of the existing research is fragmented without a common vision towards a converging paradigm. Recognizing this, this paper presents the Disaster City Digital Twin as a unifying paradigm. The four main components of the proposed Digital Twin paradigm include: multi-data sensing for data collection, data integration and analytics, multi-actor game-theoretic decision making, and dynamic network analysis. For each component, the current state of the art related to AI methods and approaches are examined and gaps are identified.

Suggested Citation

  • Fan, Chao & Zhang, Cheng & Yahja, Alex & Mostafavi, Ali, 2021. "Disaster City Digital Twin: A vision for integrating artificial and human intelligence for disaster management," International Journal of Information Management, Elsevier, vol. 56(C).
    • Handle: RePEc:eee:ininma:v:56:y:2021:i:c:s0268401219302956
    DOI: 10.1016/j.ijinfomgt.2019.102049
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    Citations

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    Cited by:

    1. Shivam Gupta & Sachin Modgil & Ajay Kumar & Uthayasankar Sivarajah & Zahir Irani, 2022. "Artificial intelligence and cloud-based Collaborative Platforms for Managing Disaster, extreme weather and emergency operations," Post-Print hal-04325638, HAL.
    2. Gupta, Shivam & Modgil, Sachin & Kumar, Ajay & Sivarajah, Uthayasankar & Irani, Zahir, 2022. "Artificial intelligence and cloud-based Collaborative Platforms for Managing Disaster, extreme weather and emergency operations," International Journal of Production Economics, Elsevier, vol. 254(C).
    3. Dubey, Rameshwar & Bryde, David J. & Dwivedi, Yogesh K. & Graham, Gary & Foropon, Cyril, 2022. "Impact of artificial intelligence-driven big data analytics culture on agility and resilience in humanitarian supply chain: A practice-based view," International Journal of Production Economics, Elsevier, vol. 250(C).
    4. Batel Yossef Ravid & Meirav Aharon-Gutman, 2023. "The Social Digital Twin:The Social Turn in the Field of Smart CitiesÂ," Environment and Planning B, , vol. 50(6), pages 1455-1470, July.
    5. Dhar, Suparna & Tarafdar, Pratik & Bose, Indranil, 2022. "Understanding the evolution of an emerging technological paradigm and its impact: The case of Digital Twin," Technological Forecasting and Social Change, Elsevier, vol. 185(C).

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