Identifying issues before they occur

Disruptions in supply, such as broken gas or water mains, are hugely costly for utilities companies in both outright financial terms and in reputational damage. Prevention is, of course, far preferable to the alternative, which can involve major disruption to customers and nearby road and rail infrastructure.

Leveraging AI to understand the causes behind historic breakages, utilities’ operation teams are able to identify patterns in the data that predict where a new break can be expected next, providing opportunities to prevent issues before they incur major costs.

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Supporting vulnerable customers

Utilities have a mandate to protect vulnerable customers from being cut-off in the event of being unable to pay bills. But it’s important that, while protecting those in rightful need, other customers don’t abuse the system, effectively passing on the costs of their unpaid bills to the wider customer base.

For the bill payer, that means less costs to be passed on, and for the business and its regulators, a clear audit trail of where issues have been identified and rectified swiftly.

AI, supported by other emerging technologies, such as the internet of things (IoT), sensors, big data and distributed ledger technology, has the ability to monitor, interpret and cross reference data sources such as bill payment patterns, customer calls, and usage, to build a picture of potential defaulters and suggest appropriate methods for utilities providers to address issues with the customer before they incur heavy debts.

Protecting critical supply

With changes in the climate and geopolitical upheaval impacting energy prices, it’s critical that we protect our essential power and water supplies. AI helps achieve this goal in two very different ways: Firstly, by maximising the efficient use of those precious resources through analysing and optimising water and gas delivery networks, and reducing asset failure through deep learning and neural networks; Secondly, through protecting essential infrastructure from malicious cyber threat.

In this instance, the physical and digital threat perimeter is enormous. Assets are often in hard-to-reach locations with minimal staff on site at any time, while a lack of investment in many operational systems often means there can be weaknesses in the industrial systems used to manage supply.

Quantum AI’s deep learning solution can actively monitor and learn every area of the network, and understand the behaviours of applications, devices and users. In doing so it  builds a ‘Digital DNA’ of each, and can automatically flag or restrict access to any device or user acting outside of known ‘norms’.

This dramatically reduces workload for the IT team, provides them with detailed information of any potential threat, and provides them with the information to actively manage those threats swiftly.