What question did this study set out to answer?

To assess the effectiveness of IoT-based sensors in monitoring air quality at mining sites in Ghana.

March 19, 2026Open Access

Sensors and IoT Systems for Environmental Monitoring in Ghanaian Mining Sites

YAYakubu AsareNoguchi Memorial Institute for Medical Research KMKhadija MusahAshesi University ADAlhassan DorkaUniversity of Professional Studies

Key Points

To assess the effectiveness of IoT-based sensors in monitoring air quality at mining sites in Ghana.
Conducted field tests at two major mining locations
Employed sensor design for real-time data acquisition
Applied machine learning algorithms for data analysis
Real-time air quality monitoring showed a 20-30% reduction in particulate matter levels
The IoT monitoring system exhibited high accuracy and reliability
Findings suggest potential for improved public health outcomes through effective environmental surveillance

Abstract

Ghana's mining industry faces significant environmental challenges such as air and water pollution, which can impact public health and ecosystem balance. A multidisciplinary approach including sensor design, data acquisition, and machine learning algorithms was employed. Field tests were conducted at two major mining sites. Real-time air quality data indicated a significant reduction (20-30%) in particulate matter levels compared to historical records, highlighting the effectiveness of the deployed sensors. The IoT-based monitoring system demonstrated high accuracy and reliability in environmental surveillance, contributing to improved public health outcomes. Further deployment should be considered across other mining sites in Ghana for comprehensive coverage and continuous improvement based on feedback loops. Environmental Monitoring, Mining Sites, IoT Systems, Sensor Technology, Air Quality The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.

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