GEOMINING-ALERT: Smart monitoring of acid mine drainage based on colorimetric strip integrated mobile-app for participatory mapping towards SDGs 2030
DOI:
https://doi.org/10.61511/aes.v3i2.2026.2374Keywords:
acid mine drainage, colorimetric analysis, citizen science, mobile environmental monitoring, Penta-Helix collaborationAbstract
Background: Acid Mine Drainage (AMD) remains one of the most severe and persistent environmental issues in post-mining landscapes, leading to acidic runoff and heavy-metal contamination that endanger aquatic ecosystems and human health. Previous studies highlight the limited accessibility of conventional monitoring tools due to their high cost and dependency on laboratory infrastructure. Therefore, this study aims to develop a participatory, low-cost monitoring framework called GEOMINING-ALERT, which integrates colorimetric strip technology and mobile-based applications for real-time AMD detection and reporting. Methods: This study employed a descriptive qualitative design-based research approach consisting of four stages: literature synthesis on AMD chemistry and participatory monitoring, prototype design of a colorimetric strip and mobile interface, integration of both components into a cloud-based dashboard, and comparative validation against existing monitoring frameworks. Data were obtained from peer-reviewed journals, technical reports, and secondary environmental databases, and analyzed using comparative synthesis to identify methodological and technological gaps. Findings: The GEOMINING-ALERT system demonstrated comparable precision to laboratory analyses, with less than 5% relative error and a 60% reduction in data reporting latency. The participatory framework increased community engagement, transparency, and environmental literacy while enhancing inter-institutional collaboration under the Penta-Helix model. Conclusion: GEOMINING-ALERT effectively bridges scientific monitoring and citizen participation, establishing a scalable early-warning system for AMD management. Novelty/Originality of this article: This study introduces a novel socio-technological model that merges colorimetric chemistry, mobile sensing, and citizen science to produce co-generated environmental intelligence, promoting inclusive sustainability toward the 2030 SDGs.
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