Fri 01 Jun 2018

Why is machine learning key to minimising water losses?

Grid system inefficiencies and leaks in old pipes could be costing US water suppliers around 16 per cent of their treated water supply, according to the Environmental Protection Agency. On the other hand, the World Bank estimates this figure could be as high as 30 per cent in developing countries. When you add the cost of avoidable repairs and maintenance to aging water infrastructure, the costs really start to stack up for water suppliers.

Minimising losses of this limited natural resource is a priority – but how can the water industry make this a reality? The answer: machine learning — intuitive water level measurement and leak detection controlled by AI.

The rise of the smart machine

In other sectors, the term ‘Industry 4.0’ is no longer just a buzz term. The automation of essential processes with intuitive, AI-controlled systems is leading the water industry to new heights of efficiency and reducing the instances of water losses by human error.

This rise of the smart machine in the workplace has also promised changes with how water suppliers are operated – Global Water Intel points to a sector report, according to which the market for water control and monitoring systems will grow to $30.1 billion by 2021.

With machine learning technology, water suppliers can leave intuitive software to monitor for leaks and blockages in the water system. This will reduce the amount spent on maintenance and repairs and will also provide intelligent guidance on how and where to update network infrastructure.

Solutions for lowering water losses

Integrating machine learning into the water utilities supply and infrastructure management policy isn’t just one for the future. Many suppliers are investing millions in implementing the right technology now to reduce their costs and enable them to focus on being a customer-driven service supplier.

Utilities software firm Franca has recently partnered with loss management solutions company Utility Services Associates to create an intuitive system to help reduce non-revenue water loss. The technology will be used to identify the worst-performing pipelines and infrastructure for preventative maintenance.

President of the Utility Services Associates Rob Meston said: ”We believe this is going to revolutionise pipe condition assessment and leak detection. It’s more important than ever to leverage technology to help guide infrastructure decisions and ensure efficient spending.”

Intuitive, AI-controlled technology is also being trialled on an individual basis to give water customers the chance to review their own use. US geographic analytics business OmniEarth is using IBM’s Watson technology to help water managers to understand how their rate payers are using water, ”It can tell you how good, bad, or ugly customers’ water usage is, who’s wasting water and where,” says Inland Empire Water Utilities’ Tom Ash. ”Then, utilities know who to target with what kind of program.”

Improving water utilities’ customer experiences

By identifying what technology can improve network efficiency, water suppliers can spend less time and fewer resources searching for and repairing leaks, and instead dedicate more time to working on improving their cost to serve, service offering and customer experience.

Suppliers who use machine learning and early-warning for leak detection can lower their maintenance and repair costs – and pass these savings on to customers. And with increased time and resources, water utilities can focus their efforts on identifying other opportunities to improve customer experiences, enabled by billing and customer services platforms such as those solutions from Gentrack.

Gentrack has long been the provider of choice for billing and customer engagement solutions to the water industry. By automating back office processes, these solutions reduce service costs, leaving water suppliers to focus on innovation and building exceptional customer experiences. For more information, chat to the Gentrack team today.