Eric Verheylewegen, VP Strategic Initiatives Enterprise and Land Mobile at Viasat, takes a look at why the water sector in showing growing interest in using satellite technology to bridge the existing “not spots” connectivity barrier for smarter water networks.

Eric Verheylewegen: Artificial Intelligence is becoming increasingly valuable to the utilities sector, already helping to reduce the loss of treated water in countries such as Japan and Singapore. From predicting pipe bursts and reducing leaks, to optimising water flow during a drought, AI could help the industry build a future of proactive, intelligent management.

Yet, these models are only as good as the data they are fed. In the UK, much of the water infrastructure - from remote reservoirs to sprawling pipeline networks - lies in a connectivity ’not spots’, making it difficult to collect and share data to and from utility assets in real time.

This is where satellite connectivity - specifically Narrowband Non-Terrestrial Networks (NB-NTN) technology - could help. Utilising industry-wide 3GPP network standards, NB-NTN allows devices to connect directly to satellites, creating a hybrid approach that can use both cellular and satellite coverage through a single SIM, without the need for specialised satellite terminals.

This makes it cost-effective and scalable to deploy smart sensors and gather data from any asset, anywhere - helping to create the consistent data stream needed to support more accurate models, and better decision-making across water networks. What’s more, recent research from Viasat shows that 63% of utility leaders plan to adopt this solution within the next 12 months, underlining growing interest in the role connectivity will play in supporting the sector’s digital ambitions.

Ageing assets, connectivity barriers, and the AI advantage

The challenge for utility 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's 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. The overhaul of UK water regulation earlier this year has brought renewed scrutiny and tougher expectations around water quality and leakage reduction, with significant financial penalties for failure.

AI and big data analytics offer a path to more proactive, preventative management, but it is intensely data hungry. 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 preventive 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.

Unlocking an always-on data flow with NB-NTN

NB-NTN is a potentially game-changing technology that enables IoT devices to connect to both cellular and satellite networks through a single, integrated module, without requiring a traditional satellite terminal. This reduces both complexity and cost of deploying IoT at scale and alters the cost/benefit analysis for organisations. For the UK's extensive water infrastructure, a constant, reliable flow of data from nearly any asset, anywhere, could now be in sight.

For the water sector, this means a more complete picture of assets across the network, wherever they are located.

Putting data to work: from leak detection to worker safety

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 a 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.

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.

This reliable, ubiquitous data stream is what makes the AI-powered predictive maintenance and forecasting a widespread reality.

A practical route to smarter water management

The case for AI in the utilities sector is evident, but the technology can only deliver value if the underlying connectivity is in place. Without reliable access to remote assets, the sector will continue to face barriers to moving beyond isolated projects into broader operational deployment.

NB-NTN can offer a practical way to address that challenge. Making satellite connectivity more accessible, cost-effective, and scalable, it affords water companies a route to extend smart monitoring across more of their network. That, in turn, supports the reliable data stream that AI systems need to improve predictive maintenance and forecasting.

As the sector continues to face pressure from ageing infrastructure, tighter regulation and increasingly unpredictable weather patterns, satellite-connected IoT can help power AI analysis and help utilities move from reactive fixes to more forward-looking management: supporting a stronger, more sustainable water system.