The cost to maintain and resolve blockages in waste and storm water systems can cost cities millions of dollars each year. In addition to the costs are the environmental, health and safety risks to the public. The nature of accessing difficult to reach pipes and infrastructure, along with the wide variety of factors that can cause chokes, leaves the traditional maintenance programs of preventative and reactive maintenance ineffective in networks that span thousands of kilometres.
By applying artificial intelligence and machine learning models to the live and historical data, VROC is able to predict the future condition of the pipe network to assist in the maintenance planning and prioritization of repairs and inspections.
VROC can also integrate with the live local weather forecasts to predict surges in storm water volumes, assisting with insights to help avoid significant events and failures.
The results from the application of Smart Waste and Storm Water management have a direct bottom line effect on the city, as well as benefits for the community and the environment, including the following;
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DataHUB4.0 is our enterprise data historian solution, OPUS is our Auto AI platform and OASIS is our remote control solution for Smart Cities and Facilities.
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Ready to embark on a pilot project or roll-out AI innovation enterprise wide? Perhaps you need assistance integrating your systems or storing your big data? Whatever the situation, we are ready to help you on your digital transformation.
The efficient deployment, continuous retraining of models with live data and monitoring of model accuracy falls under the categorisation called MLOps. As businesses have hundreds and even.
Learn more about DataHUB4.0, VROC's distributed enterprise data historian. Complete the form form to download the product sheet.
Discover how you can connect disparate systems and smart innovations in one platform, and remotely control your smart facility. Complete the form to download the product sheet.
'OPUS, an artistic work, especially on a large scale'
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