Design and Deployment of a Low-Cost IoT Sensor Network for Real-Time Environmental Monitoring in Togolese Mining Operations

{ "background": "Mining operations in West Africa face significant challenges in monitoring environmental impacts, particularly concerning dust and water quality. Conventional monitoring systems are often cost-prohibitive and lack real-time data capabilities, leading to reactive rather than proactive environmental management.", "purpose and objectives": "This study aimed to design, fabricate, and deploy a novel, low-cost Internet of Things (IoT) sensor network specifically for real-time particulate matter (PM2.5) and pH monitoring in active mining areas. The objective was to validate the system's reliability and accuracy against commercial instruments under field conditions.", "methodology": "A network of custom-built sensor nodes was developed using Arduino microcontrollers, low-cost PM2.5 optical sensors, and pH probes. Data transmission utilised LoRaWAN for long-range, low-power communication to a central gateway. The network was deployed across three operational zones within a mining site. Performance was evaluated using a linear mixed-effects model: PM2.5\\ (measured) = \β0 + \β1 PM2.5\\ (reference) + usite + \ε, with robust standard errors to account for spatial clustering.", "findings": "The IoT network achieved a mean absolute percentage error of 12.3% for PM2.5 concentrations compared to a calibrated reference instrument. The statistical model showed a strong linear relationship (\β1 = 0.94, 95% CI: 0.89 to 0.99). Spatial analysis revealed that PM2.5 levels were, on average, 28% higher downwind of the primary extraction zone compared to upwind control points.", "conclusion": "The developed system provides a viable, cost-effective solution for continuous environmental monitoring in resource-limited settings. It delivers data of sufficient accuracy for operational oversight and identifying pollution hotspots in near real-time.", "recommendations": "Mining operators should integrate such low-cost IoT networks into their environmental management plans for continuous compliance monitoring. Future work