The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Disaster City Digital Twin: A vision for integrating artificial and human intelligence for disaster management
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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.
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1 retracted
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Cited by
Collins, C., Dennehy, D., Conboy, K., & Mikalef, P. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2021.102383 · Cited by 783
Rathore, M. M., Shah, S. A., Shukla, D., Bentafat, E., & Bakiras, S. (2021) · IEEE Access · doi:10.1109/access.2021.3060863 · Cited by 616
Applications of artificial intelligence for disaster management
Sun, W., Bocchini, P., & Davison, B. D. (2020) · Natural Hazards · doi:10.1007/s11069-020-04124-3 · Cited by 491
Integrating BIM and AI for Smart Construction Management: Current Status and Future Directions
Pan, Y., & Zhang, L. (2023) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-022-09830-8 · Cited by 441
Sepasgozar, S. M. E. (2021) · Buildings · doi:10.3390/buildings11040151 · Cited by 367
Metadata
- Authors
- Fan, C., Zhang, C., Yahja, A., & Mostafavi, A.
- Venue
- International Journal of Information Management
- Publisher
- Elsevier BV
- Published
- 2021-02
- Volume
- 56
- Pages
- 102049
- ISSN
- 0268-4012 (ISSN-L)
- OpenAlex
- W2997072997
- Cited by
- 434
- References
- 66
- FWCI
- 71.70
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Fan, C., Zhang, C., Yahja, A., & Mostafavi, A. (2021). Disaster City Digital Twin: A vision for integrating artificial and human intelligence for disaster management. International Journal of Information Management. https://doi.org/10.1016/j.ijinfomgt.2019.102049
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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