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Water Main Breaks Prediction

Predictive Analysis of Water Main Breaks- Kerala Water Authority

Typically, water mains break when environmental and operational conditions exert stresses that exceed their diminishing structural resiliency. The deterioration of pipes can be affected by operational and environmental conditions, some of which are static while others vary over time.

The present technique is basically a quick assessment and repair after a pipe breaks which is a reactive approach with enormous loss in property and resources. In an industry where so many assets are buried out of sight, and where hard-earned infrastructure experience is valued, having faith in data scientists who never got their hands wet or dirty at the bottom of a trench can be difficult to accept at first. As with any other new technology, however, following step-by-step logic and proving out concepts based on performance against known results can ease concerns and build confidence in the predictive powers of AI/ML.

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In the wake of the covid 19 pandemic, all the sectors are now bouncing back and the demand for water has increased. The ground water level has decreased alarmingly . There has been a decline in water supply and distribution system due to pipe breaks .

Think Smart- Predictive analysis using AI

The beauty of ML – empowered AI is that it can start with any level of utility recordkeeping, fill in data gaps, supplement that information with data from outside sources, analyze a seemingly infinite number of relationships among all those factors, yet yield quite accurate insight on related trends.

The process includes gathering data and improving data quality to make AI most effective. It will describe the processes of machine learning. It will describe how using likelihood of failure (LoF) can be overlaid with consequence of failure (CoF) to help make better asset management decisions about pipes in the system based on risk.

Utilities have an increasing number of ways to manage assets. These include inspection, leakage monitoring, condition assessment, and an array of renewal options. A probability analysis enables prioritization that can avoid catastrophic breaks and premature replacement.

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From reducing water loss, energy consumption and cost to maintaining and extending the lifetime of the distribution network, the benefits of Forecast using AI ML is innumerable. Since we use proactive technique over reactive ones, there is a huge gain and management of resources and economical growth.

lt enables the city to better allocate resources, facilitate long-term planning, and increase cooperation between different departments such as the water department and department of public works. This combination of data science and city planning will lead to more proactive infrastructure maintenance.

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