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09/18/2024 5:50 pm

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Machine Learning Projects

Using technology to protect Raleigh's water infrastructure

Updated: Sep 18, 2024

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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 uses artificial intelligence (AI) and computer science to recognize patterns and trends in data, similar to how a human learns. This type of learning gradually improves its accuracy over time as more information becomes available. Data from machine learning projects is used to identify patterns of failure in the water system. Having this detailed information helps Raleigh Water plan for replacement projects in areas where failure is most likely to occur. Using this cutting-edge technology, Raleigh Water operations can also be more proactive when protecting our shared water system. Being able to respond quickly to system needs not only saves customers time and decreases stress; it protects the environment. Raleigh Water is proud to be one of the few utilities in the nation to use this advanced modeling system.

Xylem's Water Main Break Predictor Project

Xylem Inc uses machine learning to predict the water pipes that are most likely to break in Raleigh Water’s system. An analysis was also prepared that selected neighborhoods for water pipe replacement projects that would prevent future water system breaks. More Info. 

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

Hazen Construction prepared a machine learning analysis that predicts in real time what future wastewater flows will be at the Neuse River Resource Recovery Facility, the City of Raleigh's largest wastewater treatment facility. This project helps the facility operators make adjustments so they can handle extra flow from rainfall events.

Advanced Drainage Systems Blockage Predictor Project

Raleigh Water has a network of 51 flow meters and 5 level monitors in our shared sewer system. Advanced Drainage Systems has a machine learning analysis project that detects the earliest signs of blockages. It then predicts overflows and alerts Raleigh Water so the department can respond before an overflow occurs.

Hazen Construction's Sewer Main Failure Predictor Project

Hazen Construction is updating a sewer main failure prediction analysis, which was initially developed by a team of students from NCSU Institute for Advanced Analytics. The prediction uses Raleigh Water's past CCTV inspections to predict which sewer mains are most likely to be broken and should be inspected and repaired in the near future.

Lead Copper Rule Revision Project

Raleigh Water is leveraging a predictive model to identify the material composition of water service lines, helping to protect public health and comply with the EPA's Lead and Copper Rule Revisions (LCRR). The experts at CDM Smith and Trinnex developed the model, which predicts which service lines contain galvanized steel, a material that may require replacement. Using data from past field verifications and historical records, the model improves its accuracy over time through an continual process. This technology helps Raleigh Water prioritize inspections and replacements, ensuring efficient and proactive maintenance of its water infrastructure.

Contact

 

For more information, please contact:

Alexander Justel
Engineer

Adam Haggerty
Engineering Supervisor

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