FireHawk: An Integrated and Adaptive Model for Wildfire Management Using IoT and AI Analytics

Portugal is facing wildfire seasons of growing severity, marked by frequent ignitions, mounting economic and ecological losses, and fragmented operational strategies. Although several reforms and digital monitoring initiatives have been introduced, the country still lacks a comprehensive, real-time, and predictive framework capable of supporting adaptive wildfire management. This study presents FireHawk, an innovative system that combines edge-based Internet of Things (IoT) devices, real-time artificial intelligence (AI) analytics, and a centralized coordination platform to overcome these structural shortcomings. FireHawk integrates environmental sensors, drones, and satellite data across vulnerable territories to enable early detection, fire-behavior forecasting, and decentralized, context-driven responses. The solution merges centralized oversight—for national and strategic management—with decentralized decision-making that empowers local, autonomous interventions in rapidly evolving wildfire scenarios. Developed through a phased methodology—covering stakeholder engagement, system design, AI model training, and pilot deployments - FireHawk seeks to shift wildfire governance from a reactive, fragmented model to one that is proactive, integrated, and resilient. Beyond strengthening operational readiness, the platform delivers near-instant data fusion and simulation tools to predict fire progression. The system fosters cross-institutional collaboration by offering a unified operational view and harmonized decision-making protocols across different jurisdictions. By tackling long-standing technological and procedural fragmentation, FireHawk establishes the foundation for an intelligent, adaptive, and climate-resilient wildfire management ecosystem. Aligned with national climate adaptation priorities and the UN Sustainable Development Goals, the FireHawk framework provides a scalable template that can be replicated in other fire-prone regions worldwide.