A Context-Relevant Smart Water Quality Monitoring Testbed for Mining Communities in Ghana

Abstract

In this paper, we propose a context-relevant and task-scalable real-time water quality monitoring testbed for addressing the impacts of mining-induced water pollution issues in Ghana. The exposure of most water bodies to heavy metals such as mercury and arsenic, which are used during mineral extractions, has resulted in many health challenges in the affected communities. Many households have resorted to sinking domestic boreholes but could not address the challenge since most mine-polluted water bodies in Ghana connect to the underground water table. However, existing IoT-based water quality monitoring systems (WQMS) are founded on expensive, complex, location-restricted, hard-to-access technologies that do not suit this context by informing real-time decisions regarding the quality and usage of our water resources. To address this challenge, this paper proposes a custom-built, real-time and task-scalable IoT-based water quality monitoring testbed that is evaluated via field deployment. This technology is recommended for national policy consideration and adoption by individuals, water suppliers and industries for monitoring spatial and temporal water pollution.