Page 11 - Workshop on Reimagining Disaster Risk Reduction

Workshop on “Reimagining Disaster Risk Reduction: The Role
of Standardization and Innovative Technologies”

effective decision-making and the implementation of robust disaster response strategies.
Addressing these challenges is crucial for building resilience in vulnerable communities.

Mr Prothi further discussed various applications of artificial intelligence (AI) in disaster risk
assessment and management. AI technologies are being utilized for hazard assessment and
forecasting, enabling scenario investigations that predict hazard intensity and spatial extent17.
Additionally, AI-driven tools like InfraRivChange and the INDRA citizen science app are being
developed to monitor river migration and enhance real-time flood detection, respectively

Mr Prothi further highlighted that the Financial Decision Framework is also being established,
which utilizes disaster damage rating models based on machine learning approaches. This
framework aims to automate damage assessment and expedite financial planning and
resource allocation during post-disaster recovery. Furthermore, the document emphasizes
the importance of risk coverage and transfer mechanisms, which provide financial assistance
and facilitate insurance claims through parametric risk transfer methods.

Furthermore, the work of the Coalition for Disaster Resilient Infrastructure (CDRI) was also
presented as a global, regional, and local knowledge platform focused on disaster and climate-
resilient infrastructure. CDRI's approach includes sectoral capacity building and risk-sharing
through financial arrangements, which are essential for enhancing infrastructure resilience
against climate and disaster risks.

• Katharina Weitz, AI Researcher, (Fraunhofer HHI)

Ms. Katharina Weitz delivered a presentation discussing the importance of international
standards for AI in disaster management, emphasizing guidelines for technology use that must
be adopted into national laws to ensure interoperability and harmonization. She highlighted the
need for standardization to fill existing gaps and follow emerging trends in the field of disaster
management given the wide range of stakeholder involved in the process.

Key topics underscored in the presentation included identifying gaps in current standards
and technologies relevant to AI applications in disaster management and the role of the ITU/
WMO/UNEP Focus Group on AI for Natural Disaster Management (FG-AI4NDM) which has
developed several outputs including a standardization roadmap, glossary and various technical
reports containing best practices related to the use of AI for data management, modeling and
communication in the context of disaster management and disaster resilience. This Focus Group
is now transitioning into a Global Initiative, building upon the outputs of the Focus Group,
exploring new AI applications, updating technical reports, and developing frameworks for AI
readiness.

Several proof-of-concept projects are mentioned, including Mediterranean and pan-European
forecast and Early Warning System against natural hazards (MedEWSa), which focuses on
Mediterranean and pan-European forecasting and early warning systems against natural hazards,
and Trusted and Extremely Precise Mapping and Prediction for Emergency Management –
TEMA, which aims for precise mapping and prediction for emergency management. These
projects are funded by Horizon Europe and the European Union's research and innovation
programs and seek to implement the best practices developed by FG-AI4NDM.
• Anil Gupta Full Professor (Policy-Strategies and Capacities), ICAR

Mr Anil Gupta (ICAR) through his presentation discussed the integration of AI in disaster DRR
and crisis response, emphasizing the need for effective policy planning and capacity building.

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