New project on AI in the water sector – a strategic roadmap

2024-10-28

This fall, we are launching several new projects. The first to be granted are three that in different ways show the way forward for the water sector. We take a closer look at one of them, which deals with the topical subject of AI and machine learning in Swedish water companies.

This autumn, Mistra InfraMaint’s Board is giving the green light to new strategic projects within our program.

– We have chosen to launch a number of projects that we believe will contribute to efficient and sustainable asset management. They range from optimizing sensor placement in the network to AI and experiences from abroad, but the common thread is that they all help our water and wastewater organizations to achieve more with less,’ says Åsa Flydén, Acting Programme Manager.

Three new water projects

Three projects are already ready to start, all revolving around water and future strategies and innovation for our water infrastructure: one is about what we can learn from foreign pioneers when it comes to digitalization in the water sector and one about optimal placement of sensors in storm and wastewater networks.

The third is a roadmap for scaling up the use and adoption of AI and machine learning in Swedish water and wastewater organizations – what works, how and why does it work?

The project aims to simplify the adoption and use of AI and machine learning tools in Swedish water utilities, by evaluating current implementations, reviewing best practices and gaining expert insights. We asked project manager Emmanuel Okwoi to tell us more.

Why did you initiate this project?
– Swedish municipalities face a critical juncture in water management. The 2023 Svenskt Vatten report highlights an aging infrastructure stock and with SEK 10 billion annual investment deficit in our water and sewage infrastructure. This challenge, however, presents an opportunity for innovation.

What is the main challenge the project addresses?
– Despite the benefits of AI, there seems to be a gap between its awareness and its widespread use in practice. Bridging that gap is crucial for digital transformation in many water and wastewater organizations. The project will look at some aspects that affect the use of AI, such as data security classification and rapid technological advances – the rapid development of AI poses constant challenges in determining which algorithms, tools and best practices to use or avoid. This makes it difficult for VA organizations to implement solutions based on their specific needs and integrate them with existing systems.

What solution does the project provide?
– We want to deliver a clear, actionable roadmap that can support water and wastewater organizations in effectively using AI and machine learning methods. It will hopefully lead to more data-driven decision-making and greater efficiency – using AI to optimize processes leading to both cost savings and better resource management.

How far would you say the swedish water industry has come in terms of ai development?

– In my opinion the Swedish water industry is still in its early stages, and already showing promise in key areas such as predictive maintenance, leak detection, and water quality monitoring. Leading municipalities are pioneering these solutions, demonstrating the potential for significant improvements in efficiency and sustainability. However, challenges remain. Many utilities are grappling with data infrastructure limitations, expertise gaps, and the need to balance AI investments with urgent infrastructure renewals. Despite these hurdles, the outlook is promising.