City of Tucson Water Department employs machine learning

Aug. 6, 2020
Software from VODA.ai will support pipe condition assessment programs.

BOSTON -- The City of Tucson Water Department has selected VODA.ai as their exclusive provider of artificial intelligence software service for pipe prioritization. VODA.ai is excited to expand the partnership with the City of Tucson and provide continuous virtual condition assessment for the entire water system of over 4,600 miles of distribution water main pipes. The service includes forward-looking predictions, which are updated quarterly.

"The City of Tucson is working toward greater proactive management of our pipe inventory and VODA.ai's tools help that effort. In this challenging time, we are excited to use the cutting-edge predictive modeling from VODA.ai to help us make more informed decisions, saving water and costs," said Tim Thomure, Director of the Water Department. "There is limited data we currently have to make expensive decisions around maintaining our pipe network. With VODA.ai's daVinci machine learning technology, we will be able to make smart decisions save valuable resources and protect our water infrastructure."

"The team at Tucson Water is a great partner and works closely with us to refine the results of our daVinci engine. By expanding this partnership, we will work with Tim's team to support informed decision making to help the City continue to serve the growing population and work toward its goal of a sustainable water system," said George Demosthenous, CEO at VODA.ai.

VODA.ai's patent-pending machine learning technology discovers patterns from previous pipe failures and assigns a Likelihood of Failure (LoF) score for each pipe segment. When combined with the Consequence of Failure (CoF), the software calculates the Business Risk Exposure (BRE) for every pipe segment, allowing utilities to focus their resources on the most important assets.  VODA.ai software automatically "cleans" data of anomalies, enhancing predictive quality as well as serving other digital systems.

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