Design of Optimal Wireless Sensor Networks for Enhanced Wildfire Risk Mitigation at Wildland–Human Interfaces

Abstract

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Critical infrastructure and fire-vulnerable facilities are often located in close proximity to wildland domains, including urban settlements, human activity areas, and industrial zones. Vulnerability is frequently assessed through physical analyses of the fire's direct effects on specific types of facilities (e.g. storage tanks). However, wildfire dynamics and behaviour in the extended wildland domain are often neglected, overlooking scenarios where distant ignitions from wildfires can trigger Natech events and the release of hazardous substances, e.g., from Seveso sites, potentially leading to domino effects. Proper consideration of wildfire dynamics is essential to determine the response times required to prevent disasters. This study considers Wireless Sensor Networks (WSNs), as early detection systems, and uses wildfire simulation datasets to obtain statistical insights into response times and optimize the sensor locations accordingly. The study considers a case study of a wildland-industrial interface in Spain, including time-to-failure data on storage tanks in immediate fire proximity. Results demonstrate that early wildfire detection systems significantly enhance risk awareness, underscoring the potential of optimized WSNs for mitigating wildfire risks at wildland-human interfaces.