Raleighnc.gov logo
Thank you for printing this page from the City of Raleigh's Official Website (www.raleighnc.gov)
https://raleighnc.gov/water-and-sewer/services/machine-learning-projects
12/12/2025 8:55 am

Crew_Mic_Test

Machine Learning Projects

Using technology to protect Raleigh's water infrastructure

Updated: Dec 12, 2025

Jump To:

 
Xylem's Water Main Break Predictor Project Hazen Construction's Neuse River Resource Recovery Facility Flow Predictor Project Advanced Drainage Systems Blockage Predictor Project Hazen Construction's Sewer Main Failure Predictor Project Lead Copper Rule Revision Project

Machine learning is a type of artificial intelligence (AI) that helps computers recognize patterns in data, improving as they receive more information. Raleigh Water uses this technology to detect early signs of problems in the water system and identify areas where failures are most likely to occur.

By using these advanced tools, Raleigh Water can respond more quickly, reduce stress for customers, and better protect the environment. The utility is proud to be one of the few in the nation using such cutting-edge technology.

Xylem's Water Main Break Predictor Project

Xylem Inc uses machine learning to predict which water pipes in Raleigh Water’s system are most likely to break. They also created an analysis that identifies neighborhoods where replacing pipes now can help prevent future water system failures.

Hazen Construction's Neuse River Resource Recovery Facility Flow Predictor Project

Hazen Construction developed a machine learning system that predicts future wastewater flows at the Neuse River Resource Recovery Facility, Raleigh’s largest treatment plant. This real-time forecasting helps operators prepare for increased flow during heavy rain, allowing the facility to adjust quickly and stay efficient.

Advanced Drainage Systems Blockage Predictor Project

Raleigh Water uses 51 flow meters and 5 level monitors to track activity in the sewer system. Advanced Drainage Systems created a machine learning tool that spots early signs of blockages and predicts when overflows might happen. This system alerts Raleigh Water so crews can fix problems before an overflow occurs.

Hazen Construction's Sewer Main Failure Predictor Project

Hazen Construction is updating a sewer main failure prediction system originally developed by NCSU students. Using Raleigh Water’s past CCTV inspections, the system predicts which sewer mains are most likely to break, helping prioritize inspections and repairs.

Lead Copper Rule Revision Project

Raleigh Water uses a predictive model to identify the materials in water service lines, helping protect public health and meet EPA standards. Developed by CDM Smith and Trinnex, the model predicts which lines contain galvanized steel, which may need replacement. By learning from past inspections and historical records, the model becomes more accurate over time, helping Raleigh Water prioritize inspections and upgrades efficiently.

Contact

 

For more information, please contact:
Alexander Justel
Engineer

 

Subscribe

 
Back to Water and Sewer
Lead Department:
Water