Digital Twin and Agentic AI for Wild Fire Disaster Management: Intelligent Virtual Situation Room
On the map: LLM agents and tool use → Multimodal and embodied agents
Abstract (arXiv)
According to the United Nations, wildfire frequency and intensity are projected to increase by approximately 14% by 2030 and 30% by 2050 due to global warming, posing critical threats to life, infrastructure, and ecosystems. Conventional disaster management frameworks rely on static simulations and passive data acquisition, hindering their ability to adapt to arbitrarily evolving wildfire episodes in real-time. To address these limitations, we introduce the Intelligent Virtual Situation Room (IVSR), a bidirectional Digital Twin (DT) platform augmented by autonomous AI agents. The IVSR continuously ingests multisource sensor imagery, weather data, and 3D forest models to create a live virtual replica of the fire environment. A similarity engine powered by AI aligns emerging conditions with a precomputed Disaster Simulation Library, retrieving and calibrating intervention tactics under the watchful eyes of experts. Authorized action-ranging from UAV redeployment to crew reallocation-is cycled back through standardized procedures to the physical layer, completing the loop between response and analysis. We validate IVSR through detailed case-study simulations provided by an industrial partner, demonstrating capabilities in localized incident detection, privacy-preserving playback, collider-based fire-spread projection, and site-specific ML retraining. Our results indicate marked reductions in detection-to-intervention latency and more effective resource coordination versus traditional systems. By uniting real-time bidirectional DTs with agentic AI, IVSR offers a scalable, semi-automated decision-support paradigm for proactive, adaptive wildfire disaster management.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Multimodal and embodied agents, one of 16 directions in LLM agents and tool use. Builds on 22 of its 157 references that are in the map. First posted on arXiv 9 Feb 2026.
Builds on
22 of 157 references.
References · 22
- 2023BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Modelscited by 6,069
- 2024LLM-Assisted Crisis Management: Building Advanced LLM Platforms for Effective Emergency Response and Public Collaborationcited by 20
- 2024Decision support system for Forest fire management using Ontology with Big Data and LLMscited by 6
- 2020Transfer Learning as an Enabler of the Intelligent Digital Twincited by 4
- 2025Leveraging Large Language Models for Enhanced Digital Twin Modeling: Trends, Methods, and Challengescited by 4
- 2025Comparative and Interpretative Analysis of CNN and Transformer Models in Predicting Wildfire Spread Using Remote Sensing Datacited by 4
- 2018EdgeChain: An Edge-IoT Framework and Prototype Based on Blockchain and Smart Contractscited by 3
- 2022An Overview of Cyber Threats, Attacks, and Countermeasures on the Primary Domains of Smart Citiescited by 2
- 2023An Ensemble Machine Learning Approach for Tropical Cyclone Detection Using ERA5 Reanalysis Datacited by 2
- 2023Digital Twinning in Smart Grid Networks: Interplay, Resource Allocation and Use Casescited by 2
- 2024Facilitating AI and System Operator Synergy: Active Learning-Enhanced Digital Twin Architecture for Day-Ahead Load Forecastingcited by 2
- 2024Synthetic imagery for fuzzy object detection: A comparative studycited by 2
10 more
- 2024Use Digital Twins to Support Fault Diagnosis From System-level Condition-monitoring Datacited by 2
- 2024TwiNet: Connecting Real World Networks to their Digital Twins Through a Live Bidirectional Linkcited by 2
- 2024Predictive Digital Twin for Condition Monitoring Using Thermal Imagingcited by 2
- 2025Enhancing Disaster Resilience with UAV-Assisted Edge Computing: A Reinforcement Learning Approach to Managing Heterogeneous Edge Devicescited by 2
- 2021Digital Twin Based Disaster Management System Proposal: DT-DMScited by 1
- 2023Estimating fire Duration using regression methodscited by 1
- 2023Smart City Digital Twin Framework for Real-Time Multi-Data Integration and Wide Public Distributioncited by 1
- 2024Evacuation Management Framework towards Smart City-wide Intelligent Emergency Interactive Response Systemcited by 1
- 2024Contaminant Dispersion Simulation in a Digital Twin Framework for Critical Infrastructure Protectioncited by 1
- 2025Data Taxonomy Towards the Applicability of the Digital Twin Conceptual Framework in Disaster Managementcited by 1
Built on by
Not cited yet.
Similar, not cited
Close in wording, no citation either way
- 2026VULCAN: Vision-Language-Model Enhanced Multi-Agent Cooperative Navigation for Indoor Fire-Disaster Response ↗
- 2025Generative AI as a Pillar for Predicting 2D and 3D Wildfire Spread: Beyond Physics-Based Models and Traditional Deep Learning
- 2025CREW-WILDFIRE: Benchmarking Agentic Multi-Agent Collaborations at Scale
- 2026FIRE-VLM: A Vision-Language-Driven Reinforcement Learning Framework for UAV Wildfire Tracking in a Physics-Grounded Fire Digital Twin
- 2025Disaster Management in the Era of Agentic AI Systems: A Vision for Collective Human-Machine Intelligence for Augmented Resilience
- 2025A RAG-Based Multi-Agent LLM System for Natural Hazard Resilience and Adaptation
- 2026A Simulation-Grounded Agentic VLM Framework for Wildfire Monitoring and Reporting
- 2026Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations