Abstract
Wireless sensor networks (WSN) are essential for monitoring operations, environmental conditions, and ensuring worker safety in underground mining environments. A key challenge in deploying these networks lies in achieving sufficient sensor coverage and reliable connectivity to enable early incident detection and timely response. While existing approaches primarily focus on deployment efficiency, this paper introduces a safety-driven optimization model that accounts for the complete underground mine structure and its specific operational conditions. The proposed algorithm minimizes the number of deployed nodes—reducing capital expenditure (CAPEX)—while meeting occupational safety standards by ensuring sensor coverage at critical points of interest and maintaining network connectivity. Compared to existing models, our method reduces the number of required nodes by up to 82%, while satisfying both k-coverage and k-connectivity requirements. Unlike conventional strategies based on idealized assumptions, our approach is tailored to the real-world conditions of Colombian underground mines. Simulation results demonstrate that achieving connectivity demands more nodes than coverage when both are evaluated under equivalent conditions. The algorithm was validated in two prototype mines, achieving k = 2 for both coverage and connectivity—ensuring that each point of interest is monitored by at least two sensors and connected via two link-disjoint communication paths. This redundancy enhances fault tolerance by providing backup for both sensing and communication. Finally, we introduce two new metrics for evaluating k-coverage and k-connectivity, designed to assess the robustness of WSN in underground mining and tunnel environments.
Funding Information
  • Natural Sciences and Engineering Research Council of Canada
  • Ministerio de Tecnolog?as de la Informaci?n y las Comunicaciones
  • Agencia Nacional de Investigaci?n y Desarrollo

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