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| Format: | Recurso digital |
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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.19675066 |
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Table of Contents:
- <p class="MsoNormal"><span>Water testing has historically been fragmented, with different tools, workflows, and laboratories required for different contaminants or quality indicators. This model can be effective for specialized investigations but is difficult to scale for routine, geographically dense, and repeat monitoring across households, communities, schools, utilities, NGOs, and field teams. A more practical long-term approach may be modular environmental intelligence platforms that share common hardware, software, and data infrastructure across multiple analytes.</span></p> <p class="MsoNormal"><span>This paper outlines a smartphone-based framework initially developed for microplastic and nanoplastic detection and expandable to additional targets including turbidity, copper, lead, arsenic, surfactants, PFAS, and future analytes. The central concept is a reusable backbone: sample collection, reagent interaction (when needed), smartphone imaging, computational analysis, and geospatial data integration. Microplastics and nanoplastics serve as a flagship proof-of-capability because they represent one of the most challenging categories for field detection. If a platform can address that challenge, expansion to additional targets becomes increasingly practical.</span></p>