Early Warning System for Water Infrastructure Problems

Fellows: Benjamin Brooks, Avishek Kumar, Syed Ali Asad Rizvi
Data Science Mentor(s): Ali Vanderveld, Kevin Wilson
Project Manager: Chad Kenney
Project Partner: City of Syracuse
[Short Presentation Video] [Project Blog Post] [Paper]

Many American cities currently struggle with replacing rapidly aging infrastructure on a limited budget. Syracuse, New York, has 500 miles of water mains running through the city, with some dating back to the 19th century. Replacing that crumbling water system would cost over $1 million per mile, and the need is urgent, as Syracuse experiences nearly 400 water main breaks per year.

In 2016, DSSG worked with the City of Syracuse to create a data-driven process for proactively repairing their most vulnerable water mains first. Using data on the water system, streets, work orders, and service calls, we created a predictive model that the city can use to replace or repair water mains before they fail. The analysis can also help the city make decisions about the kinds of replacement mains that are best suited for different locations and environments, and help coordinate activities between departments to get the most infrastructure work done in a single dig.

You can read more about this project here as well as on our website.