Real-Time IoT-Enabled Decision Support for Forest Supply Chains: An Optimization-Simulation Approach to Mitigating Wildfire Risk

Climate change has intensified wildfire risk, creating an urgent need for integrated, data-driven tools that connect forest operations with fuel-reduction strategies. This paper introduces a real-time IoT-enabled Decision Support System (DSS) that unifies wood traceability with optimization–simulation planning for biomass collection and processing. The system captures detailed operational data from harvesting, transportation, and processing through IoT devices and industry formats, enabling the continuous monitoring of wood flows and precise estimation of biomass residues that directly contribute to wildfire fuel loads. The DSS transforms these real-time streams into actionable planning outputs through an optimization–simulation module that generates efficient biomass harvesting and processing schedules while evaluating their robustness under wildfire-related constraints. By linking wood traceability with biomass logistics, the system provides the missing operational bridge between forest management decisions and wildfire-risk mitigation. Results show that the DSS not only improves operational efficiency but also enhances resilience by supporting risk-aware planning, prioritizing high-exposure areas, and reducing the accumulation of hazardous biomass. These insights demonstrate how digital traceability and robust planning can work together to lower ignition potential while maintaining service levels and operational continuity. Overall, this work presents a practical and scalable solution that strengthens forest supply chain resilience and provides a new pathway for integrating wildfire-risk mitigation into everyday operational planning.