ActiveRemediation
Jacob Abernethya b, Alex Chojnackic, Arya Farahic, Eric M. Schwartzc, Jared Webbd
- aGeorgia Institute of Technology &
- bUniversity of Michigan, Atlanta, GA, USA
- cUniversity of Michigan, Ann Arbor, MI, USA
- dBrigham Young University, Provo, UT, USA
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Abstract
We detail our ongoing work in Flint, Michigan to detect pipes made of lead and other hazardous metals. After elevated levels of lead were detected in residents' drinking water, followed by an increase in blood lead levels in area children, the state and federal governments directed over $125 million to replace water service lines, the pipes connecting each home to the water system. In the absence of accurate records, and with the high cost of determining buried pipe materials, we put forth a number of predictive and procedural tools to aid in the search and removal of lead infrastructure. Alongside these statistical and machine learning approaches, we describe our interactions with government officials in recommending homes for both inspection and replacement, with a focus on the statistical model that adapts to incoming information. Finally, in light of discussions about increased spending on infrastructure development by the federal government, we explore how our approach generalizes beyond Flint to other municipalities nationwide.
TL;DRThis work details the ongoing work in Flint, Michigan to detect pipes made of lead and other hazardous metals, and describes the interactions with government officials in recommending homes for both inspection and replacement with a focus on the statistical model that adapts to incoming information. (Semantic Scholar)