VODA.ai

About

A Compelling Case Infrastructure management is a challenge for municipalities and water utilities. Managers and engineers want to create effective operating and capital planning programs to lower their non-revenue water and greenhouse gasses, improve customer satisfaction, and keep their workers safe, while staying within their budget. Yet up to 70% of water is lost due to pipe failures, customer service is disrupted with each break, emergency crews are often called in during night hours, insurance often has to pay for damages, and pipes that are replaced often have over 5 years of remaining life left, incurring costs that could have been used elsewhere. A Cost-Effective and Accurate Solution VODA.ai helps municipalities and water utilities lower their non-revenue water and greenhouse gases, improve their customer satisfaction, and keep their workers safe, while staying within their budget. Their software uses Artificial Intelligence to assess the risk of every pipe in a utility for the next 12 months – for operations programs – and up to 10 years – for engineering plans. VODA.ai software includes a custom-built predictive engine called daVinci and its validated results are up to 4x more accurate than the historical breaks model. VODA.ai is an affordable tool that prioritizes every pipe segment. By filtering the top percentage on the pipe prioritization, it correctly identifies over most of the breaks before they occur, many of which take place on pipes that never broke before. How It Works VODA.ai’s software assesses the condition of every pipe segment with daVinci ML. VODA.ai uses a three-step process: At the first step, it combines utility data on pipes (e.g.: installation year, material, size, location, and break history) with public data (weather, soil, land use, satellite imagery and infrared scans, etc.), and with proprietary interaction variables. At the second step, utility data is cleaned and normalized. Using proprietary automation, data quality and completeness is assessed and enhanced. This data audit enhances many digital applications used by GIS and engineers at utilities, an added benefit derived from daVinci ML. At the third and final step, daVinci ML uses over 100 algorithms to find patterns and insights from previous breaks and assigns a Likelihood of Failure score for each pipe segment. Model accuracy improves with additional data and time. The entire process takes 4-6 weeks to complete. Utilities receive access to the VODA.ai cloud platform with an interactive map and reports on the pipes with the Likelihood of Failure of each pipe in the next 1-20 years. Full integrations with GIS systems like VODA.ai’s partner ESRI, are also available. Subscriber data and predictions are automatically updated quarterly. Utilities have the option to add their critical assets (fire stations, hospitals and other high-profile locations near pipes with high LoF) to determine community and business risks. VODA.ai shows a final risk score on each pipe segment, making it easy for utilities to plan their operating and engineering programs. For operations teams, in areas with high risk, visual inspections follow. A valuable next step is to test valve readiness near the highest risk pipes to ensure the valves are ready if a break happens. Using correlators or placing leak detector sensors in select locations makes leak monitoring effective and affordable. For engineering teams, with an average cost of $ 1 million per mile to replace pipes in the U.S., capital planners are obliged to select the right pipes for replacement. Like operations, the engineering team needs to review high risk pipes. Field conditions assessments may follow with a plan of pipe replacement as needed.