Technological advancements in sensors, wireless communications, real time data analytics, and other web services are providing new tools to study environmental systems. Leveraging these advancements, this project focused on developing an end-to-end platform to study drinking water systems.

Specifically, throughout this project we designed, built, and deployed sensor nodes in nearly three dozen single-family homes in Ann Arbor, MI, USA and in Mexico City, Mexico. These deployments have shown us the value of high spatiotemporal resolution water quality measurements through the detection of system-wide events, hydraulic and water quality monitoring. The devices and data have also proven ability to approximately measure different concentrations of residual disinfectant and record disparities of water supply experienced in intermittent systems.

This collaborative study with Prof. Branko Kerkez focused on the application of our platform to understanding dynamics of water use inside buildings and its implications on water quality experienced at the tap. With this knowledge, sensor nodes will be able to adaptively flush building plumbing systems in real time using real-time sensor signals, wireless valves, and machine learning algorithms when water quality standards are not met – opening doors into a new generation of smart building water quality management. Our hope is that this open-source platform may be used by researchers and practitioners in other fields to study unique problems at the confluence of our fields.