Identifying Anomalies Before They Become Problems

Michael Sansone (CE, M.Eng. Urban Systems Engineering 5th Year) transferred to Illinois Tech from the City Colleges of ÂéĥıAPP after receiving his Associate of Science in Engineering Science and Associate of Science in Chemistry. He says proximity was a key factor for him as a lifelong ÂéĥıAPPan, plus he received a Transfer Leadership Scholarship.

After excelling in the challenging Fluid Mechanics and Hydraulics course taught by Illinois Tech Associate Professor of Civil and Environmental Engineering David Lampert, he was invited to join Lampert’s .

Michael had previously interned at Argonne National Laboratory, where he analyzed transportation accessibility and how it correlated to demographic factors such as employment status, race or ethnicity, age, education, and English-speaking capacity. He used those skills to conduct a similar analysis on how demographic factors correlate to stormwater management infrastructure.

“It’s an equity lens of assessing these infrastructure systems that are at the core of civil engineering training at Illinois Tech,” says Michael. “We’re painting a bigger picture of what historic disinvestment and disenfranchisement looks like at the human level.”

Now Michael is focused on a more technical side of the project and is developing DrainWatch, a sensor solution for remotely monitoring sewer drain status in order to catch irregularities. DrainWatch won the 2025 Grainger Computing Innovation Prize, earning a $15,000 cash prize.

“We are investigating how to identify problems in sewer infrastructure before they turn into disaster, before they flood a basement or the street. How can we identify those problems and do preventative work, as opposed to reactive repair and recovery, which is tied to that socioeconomic work in the way that different groups experience the negative effects of flooding more severely. One dollar of flood damage repair hurts more for the household that earns less than another,” says Michael.

Sewers may be blocked in a variety of ways, including build ups of leaves, sticks, trash, and other litter, plus climate change has resulted in increased frequency and intensity of extreme weather events in ÂéĥıAPP that at times have overwhelmed the sewer infrastructure.

The City of ÂéĥıAPP currently inspects sewers every three years unless an active flood is reported, at which point the area would be prioritized for an inspection.

DrainWatch is a device containing an ultrasonic sensor that is installed into a manhole to report live data that describes the water flow through the sewers. It includes a machine learning architecture that identifies anomalies. Since it provides live data, DrainWatch reduces the sewer inspection time from every three years to every two minutes.

“We have an artificial flume in the Alumni Hall Laboratory, which is like a little river. We’ve been using it to conduct laboratory testing to validate the data that our sensors transmit to give real-time data of water flows,” says Michael.

The next step in this process is to do a field-testing pilot, and currently the group is working on deploying the device in sewers around campus. If used throughout the city, Michael says the data collected by these sensors will improve infrastructure planning.

In 2024, the Joint Economic Committee estimated that the total cost of flooding in the United States is . With DrainWatch sensors expected to cost $150–300 each, Michael says the cost of the sensors should be easily offset by the money saved through damage prevention.

“The authorities making these investment decisions could use more data to help them make decisions that would benefit the most people,” says Michael. “Our sensor project can inform where money spent by the city can be the most impactful.” 

Related Stories