The future of drinking water management was on full display last week as leading international experts gathered at The University of Sheffield for the prestigious Computing and Control for the Water Industry (CCWI) conference. Among the highlights were several presentations showcasing how artificial intelligence, machine learning, and digital twins are being harnessed to create safer and more efficient water systems.
Researchers affiliated with the Horizon 2020 project ToDrinQ and Delft University of Technology’s DRACO initiative presented four papers that signal a major shift towards a digitised water sector.
One of the key contributors, who served on both the conference’s scientific and organising committees, presented three ToDrinQ-funded studies. The research addressed critical industry challenges, including a design tool for flexible treatment plants capable of adapting to changing conditions, a machine learning model to optimise the complex ozonation disinfection process, and a comprehensive digital twin platform for real-time water quality monitoring.
In a particularly forward-looking presentation, the conference also saw the introduction of research from the DRACO initiative, exploring the application of Large Language Models (LLMs)—the same technology behind systems like ChatGPT—for urban water systems. Authored principally by Riccardo Taormina, the paper opens a new frontier for how data is interpreted and utilised in the sector.
