Designing Field-Deployable, AI Smartphone-Based Diagnostics for Global Scalable Water Intelligence: The EcoExposure Platform

Water quality monitoring is essential for public health, environmental stewardship, food systems, and climate resilience. Yet many current testing workflows remain centralized, infrastructure-heavy, episodic, and inaccessible for routine use outside specialized laboratories. This creates a global data gap: contamination events may be missed, geographic coverage remains sparse, and many communities lack practical access to timely information. Microplastics and nanoplastics exemplify the urgency. These persistent particles are now found throughout oceans, rivers, tap water, and human tissues. They can adsorb toxins, trigger inflammation, disrupt endocrine function, impair reproduction in marine species, and enter the food chain, ultimately reaching humans through seafood, drinking water, and inhalation. The EcoExposure platform was designed as a different model. Rather than beginning with laboratory instrumentation and attempting to miniaturize it, the system was conceived around real-world user constraints: no extra hardware, minimal training, rapid workflows, smartphone-native operation, and scalable deployment. The platform combines simple assay chemistry, smartphone imaging, and computer vision to enable portable environmental testing with future extensibility across multiple analytes, including microplastics/nanoplastics (flagship), PFAS (“forever chemicals”), copper, lead, arsenic, surfactants, and turbidity. This paper outlines the design logic behind the EcoExposure system, the importance of user-centered field diagnostics, and the broader vision of distributed water intelligence generated through everyday mobile devices.