# Context-Aware Multi-Agent Architecture for Wildfire Insights

## TL;DR

This paper introduces a multi-agent AI system that uses diverse environmental data to provide wildfire insights and improve decision-making for mitigation.

## Contribution

A novel orchestrator-based multi-agent system with LMMs and RAG pipelines for transparent, context-aware wildfire analysis.

## Key findings

- The system achieved a precision of 0.797 and an F1-score of 0.736 on public datasets.
- It integrates satellite imagery, sensor data, and weather information for Visual Question Answering.
- The framework supports cross-modal reasoning and transparency in wildfire risk assessment.

## Abstract

Wildfires are environmental hazards with severe ecological, social, and economic impacts. Wildfires devastate ecosystems, communities, and economies worldwide, with rising frequency and intensity driven by climate change, human activity, and environmental shifts. Analyzing wildfire insights such as detection, predictive patterns, and risk assessment enables proactive response and long-term prevention. However, most of the existing approaches have been focused on isolated processing of data, making it challenging to orchestrate cross-modal reasoning and transparency. This study proposed a novel orchestrator-based multi-agent system (MAS), with the aim of transforming multimodal environmental data into actionable intelligence for decision making. We designed a framework to utilize Large Multimodal Models (LMMs) augmented by structured prompt engineering and specialized Retrieval-Augmented Generation (RAG) pipelines to enable transparent and context-aware reasoning, providing a cutting-edge Visual Question Answering (VQA) system. It ingests diverse inputs like satellite imagery, sensor readings, weather data, and ground footage and then answers user queries. Validated by several public datasets, the system achieved a precision of 0.797 and an F1-score of 0.736. Thus, powered by Agentic AI, the proposed, human-centric solution for wildfire management, empowers firefighters, governments, and researchers to mitigate threats effectively.