Disaster City Digital Twin: A vision for integrating artificial and human intelligence for disaster management
By Chao Fan, Cheng Zhang, Alex Yahja, A. Mostafavi. International Journal of Information Management, 2021
386 citations recorded by the source corpus.
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.
Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems and Management
View Paper: https://www.semanticscholar.org/paper/04dfdf49d2e3cfce31b3544b8fe45c1d9533a82b
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In Artificial Intelligence
- Dhirendra Shukla
- Elmahdi Bentafat
- Spiridon Bakiras
- M. Mazhar Rathore
- Bilal Abu-Salih
- Syed Attique Shah
- Samad M. E. Sepasgozar
In Computer Networks and Communications
In Information Systems and Management
Citations in the corpus
- Domain-specific Knowledge Graphs: A survey (2020, background): “More advanced technical solutions have been also importing KGs to build sophisticated systems in various fields of engineering [126].”
- Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment (2021, methodology): “, radar, laser, or lidar), multi-source and homogeneous data, apply multi-actor game-theory decision algorithms considering dynamic factors [93]; connecting energy networks; decentralised digital twin models [94] and integration with blockchain.”
- The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities (2021, background): “Furthermore, DT technology may advance the disaster management approaches in smart cities [66].”
- City Digital Twin Potentials: A Review and Research Agenda (2021, methodology): “proposed using dynamic network analysis for visualizing network dynamics within a disaster in a city digital twin [50].”