Xylem Water Main Break Prediction Project Hazen Construction’s Neuse River Resource Recovery Facility Flow Prediction Project Advanced Drainage System Blockage Prediction Project Hazen Construction’s Sewer Main Break Prediction Project Lead Copper Code Revision Project
Machine learning is a type of artificial intelligence (AI) that allows computers to recognize patterns in data and improve as it receives more information. Raleigh Water uses this technology to detect early signs of problems in water systems and identify areas most likely to fail.
These advanced tools allow Raleigh Water to respond faster, reduce stress for customers, and better protect the environment. The utility is proud to be one of the few utilities in the country that uses such cutting-edge technology.
Xylem Water Main Break Prediction Project
Xylem Inc uses machine learning to predict which water pipes in Raleigh Water’s system are most likely to break. We also created an analysis that identifies areas where replacing pipes now could prevent future water system failures.
Hazen Construction’s Neuse River Resource Recovery Facility Flow Forecasting Project
Hazen Construction has developed a machine learning system to predict future wastewater flows at Raleigh’s largest treatment facility, the Neuse River Resource Recovery Facility. This real-time forecast allows operators to prepare for increased flow during heavy rain events, allowing facilities to quickly adjust and maintain efficiency.
Advanced drainage system clogging prediction project
Raleigh Water uses 51 flow meters and five level monitors to track activity within its sewer system. Advanced Drainage Systems has created a machine learning tool that finds the early signs of a clog and predicts when an overflow will occur. This system alerts the lorry water so crews can resolve the problem before an overflow occurs.
Hazen Construction’s Sewer Main Failure Prediction Project
Hazen Construction is updating a sewer main failure prediction system originally developed by NCSU students. The system uses Raleigh Water’s past CCTV inspections to predict which sewer mains are most likely to break, helping prioritize inspections and repairs.
Lead and Copper Regulation Revision Project
Raleigh Water uses predictive models to identify substances in water pipes to help protect public health and meet EPA standards. Developed by CDM Smith and Trinnex, this model predicts which lines contain galvanized steel that may need to be replaced. By learning from past inspections and historical records, the model becomes more accurate over time, helping Raleigh Water efficiently prioritize inspections and upgrades.
