Artificial intelligence has the potential to bring significant safety, sustainability and efficiency benefits to utilities. It can help operators detect leaks sooner, anticipate equipment failures, optimise water flows, and make better-informed decisions across increasingly complex networks, says Eric Verheylewegen, VP Strategic Initiatives Enterprise and Land Mobile, Viasat.
These benefits cannot come soon enough, as utilities across the UK and Europe face extraordinary pressure from record-breaking hot and dry spells alongside increased demand from, ironically, AI data centres themselves.
Yet, as recent industry analysis shows, AI can only deliver at scale in the sector when it is built on a robust, joined-up data foundation.
This is difficult when critical infrastructure is spread across remote reservoirs, pumping stations, treatment works and pipeline networks. Many of these sites fall outside of reliable cellular coverage. If data is missing, delayed or only collected intermittently, AI tools cannot develop the detailed and accurate operational picture required to spot patterns early and provide meaningful insight.
New satellite technology can offer a way to bring more of these assets into view. By enabling both terrestrial and satellite connectivity through a single IoT device with an integrated module and chipset, newly-developed IoT capabilities can extend monitoring beyond the reach of cellular networks — without the need for traditional satellite terminals.
The latter feature is a crucial part of the package; not only reducing the complexity but changing the calculation for return on investment and unlocking mass scale.
The result is a more continuous flow of operational data, giving water companies a stronger platform on which to deploy AI-driven monitoring and preventative maintenance, helping the sector preserve and protect an increasingly important resource.
Why connected data matters for ageing water networks
The challenge for utilities companies and their infrastructure is twofold: it is ageing and remote. This combination results in hard-to-detect leaks, bursts, and inefficiencies which are difficult to manage proactively, leading to reduced supply, costly disruption, and even pollution in some cases.
Without real-time monitoring across these vast networks, it is tough to pinpoint where and why problems occur. This has understandably led to a reactive approach, with companies playing catch-up to fix problems, rather than preventing them. At a time of evolving water-sector regulation and stronger expectations around environmental performance, leakage reduction and infrastructure resilience, the case for identifying problems sooner is becoming increasingly pressing.
AI and big data analytics offer a path to more proactive, preventative management, but both depend on a high volume of timely, reliable information. With a constant stream of data, AI platforms can detect leaks reliably, predict when and where pipes might fail, and identify the weakest sections of the network for preventative maintenance. By moving from a reactive to a proactive model, firms can reduce waste, avoid costly environmental fines, and build a more resilient and cost-efficient network.
But AI is only as effective as the data you can gather. That data is then worthless if you cannot reliably connect all your assets and get a clear picture of what is happening on the network. By nature, many parts of the UK’s water network are in remote areas where terrestrial connectivity is limited or non-existent, creating a significant barrier to deploying these smart solutions at scale
Extending visibility beyond cellular coverage with NB-NTN
Narrowband Non-Terrestrial Networks (NB-NTN) is a new technology being implemented by the satellite industry, following interoperable, global 3GPP standards. For the first time, NB-NTN enabled IoT devices can connect to both cellular and satellite networks through a single, integrated chipset and module. This means devices used for tracking, monitoring and control – like water meters and remote pumps for example – do not require two separate, additional, satellite and cellular terminals to connect. This can of course make deployments far simpler and more cost effective. It is a potentially game-changing technology that can enable mass scale deployments for the first time.
For water networks which stretch across both densely populated areas and remote locations, this could make near-continuous data collection from a far wider range of assets actually achievable. With NTN technology, monitoring a utility network at scale, and connecting the equipment reliably, is in reach.
For the water sector, this means a more complete picture of assets across the network. Once you are gathering much more data reliably, you can then begin powering advanced machine learning and AI techniques to deliver operational insights. And, as we know, insight equals efficiency.
Turning data into earlier intervention
By providing a reliable stream of data and reducing complexity through standards-based innovation, NB-NTN acts as the channel through which AI systems can access that vast reservoir of data and truly transform water management.
Our research found that water infrastructure monitoring was ranked as a top transformative use case by 43% of utility leaders. In practice, that means sensors can track flow and water quality in real-time, flagging leaks or contamination as soon as they appear. Beyond monitoring, this connectivity also enables proactive control, allowing operators to remotely manage pumps and valves without costly and time-consuming site visits, which is crucial for managing resources during droughts.
This reliable, ubiquitous data stream is what makes AI-powered predictive maintenance and forecasting a widespread reality.
The benefits extend to health and safety, another key priority for the sector. With 41% of leaders identifying ‘people tracking’ as a key use case, NB-NTN-connected devices can also ensure lone workers in remote locations are safe and can call for help in an emergency, regardless of cellular coverage.
From AI ambition to operational resilience
AI offers water companies a powerful opportunity to improve how they manage ageing assets, respond to pressure on supplies, and reduce avoidable disruption. But before its full value can be realised, the sector needs the joined-up, dependable data foundation on which effective AI depends.
NB-NTN provides a practical route to extending that foundation into locations beyond the reach of conventional networks. By making satellite connectivity more accessible, cost-effective, and scalable, it can help water companies bring more remote assets into view and support the continuous data flow required for smarter monitoring, predictive maintenance and forecasting.
As scrutiny of water-sector performance continues and weather patterns become more extreme and unpredictable, connecting the whole network will be central to moving from reactive repairs to more resilient, forward-looking water management.
