A point-of-use drinking water quality dataset from fieldwork in Detroit, Michigan

Abstract

Abstract Drinking water quality sensor technology has rapidly advanced, facilitating the collection of rich datasets and real-time analytics. However, sensors have not yet been widely applied to monitor drinking water quality in premise plumbing. Richer quality of data in premise plumbing offers an improved understanding of the quality of drinking water present at the point-of-use. In this paper, online drinking water quality sensor nodes were temporarily installed in twenty-four homes in Detroit, Michigan. The water quality sensor nodes took measurements of five drinking water quality parameters every five minutes for four weeks. Additionally, free chlorine and lead were sampled periodically within each home. Together, these data make up a dataset that captures drinking water quality over time in a legacy city with an oversized drinking water system. This dataset offers more frequent measurements amongst more sample homes than are typically available in premise plumbing or at the tap. The data can be used to investigate temporal trends in drinking water quality, including diurnal patterns and anomaly detection. Additionally, this dataset could be utilized to evaluate water quality in comparison with other cities.