Summary

Since 2019, Open Geospatial Consortium (OGC) has invested in geospatial data and technology pilots to advance in the areas of Climate Resilience and Disasters. The Open Geospatial Consortium is an international voluntary consensus standards organization for geospatial content and location-based services, sensor web and Internet of Things, GIS data processing and data sharing. 

For the 2024 iteration, the Climate and Disaster Resilience Pilot 2024 (CDRP24) is focused on delivering impacts. These impacts are delivered via interoperable geospatial technologies and standards. All of which is to help combat climate and disasters. CDRP24 consists of individual threads that each work towards specific end-user, stakeholder, and technical goals that advance our climate and/or disaster understanding and readiness while also seeding collaboration between these two related domains. One of the components is seeking guidance on Generative AI in Disaster Management. Xentity is requested to provide an engineering report on targeted areas GenAI can augment Wildland Fire Management Data challenges.

Problem and Solution

The integration of Generative AI (GenAI) into wildland fire (WF) management presents a transformative opportunity to enhance preparedness, response, and recovery efforts. In this report, we will delve into the challenges faced by the WF community. Also, how the adoption of GenAI can mitigate or enhance these challenges. We’ll explore the potential benefits of GenAI within the National Incident Management System (NIMS) structure and provide recommendations for its adoption.

Generative AI is in its early stages and evolving rapidly, with challenges such as error management and prompt generation persisting. Moreover, adoption within the WF community may face hurdles due to rapid technological changes, legislation, and trust issues. Data augmentation and maintenance, along with ethical considerations, pose additional challenges, requiring a focus on MLOps and data governance. To address these challenges, a structured approach to GenAI adoption within the WF community involves aligning capabilities with the NIMS phases, ensuring targeted AI solutions for core stakeholders. Appendices provide core data needs, reference models, potential data sources, and field tools, ensuring a comprehensive approach to GenAI implementation. The conceptual solution will also tie into known US data sources, systems, reference models, and candidate GenAI tools.

Outcome and Benefit

The adoption of Generative AI within the WF community promises significant benefits. Its creativity and personalization abilities enable detailed fire behavior visualizations, optimizing resource allocation and response strategies. Adaptability and problem-solving skills aid in anticipating fire spread and behavior, minimizing damage. Emotional intelligence fosters empathetic interactions within firefighting teams, while multi-modal understanding integrates real-time geospatial data for comprehensive assessments. Ultimately, the integration of GenAI promises to revolutionize WF management, enhancing resilience and effectiveness in combating wildfires.

We followed on Phase 1 with a Phase 2 Gen AI For Wildfire State-of-the-Art Report deliverable builds on Xentity’s expertise and contributions to Phase 1 (D-123) for advancing the integration of Generative AI (GenAI) technologies into wildfire risk, hazard, and insurance workflows.GenAI’s Transformative Potential though still maturing, GenAI’s human-in-the-loop approach can radically scale data processing and deliver faster, more accurate insights. The Phase 2 report focuses on By focusing on Phase 2 priorities, combined with Phase 1 inputs, which provides a forward-looking roadmap for GenAI adoption in wildfire resilience and risk management including consideration of the following on how state-of-the-art GenAI technologies elevate wildfire insurance.

The OGC approved Phase 1 and Phase 2 report publications are posted.