iOLE: Intelligent Online Leak Detection to Reduce Water Losses

The project "iOLE – Intelligent Online Leak Detection“ led by Andrea Cominola, ECDF Professor of "Smart Water Networks" at the Technische Universität Berlin, offers digital solutions for water conservation by detecting and locating emerging leaks as quickly, automatically, and reliably as possible. The aim is to sustainably minimize their consequences. The project began on September 1, 2023, and is expected to run until January 31, 2026.

“Early and precise detection and localization of leaks can significantly reduce water losses in distribution networks – currently, these losses exceed 120 million cubic meters per year worldwide and cause costs of over 39 billion US dollars annually. To accelerate this process, we are developing a user-centered software platform that integrates two award-winning algorithms from our previous research. By combining their strengths into a user-friendly dashboard, we aim to provide water utilities with a powerful tool – one with strong potential for broad adoption both in Germany and globally,” explains Andrea Cominola.

The iOLE project brings together the expertise of the Einstein Center Digital Future, Technische Universität Berlin, Urban Impact, the Kompetenzzentrum Wasser Berlin, and GELSENWASSER AG. At the core of the project are two scientifically acclaimed leak detection algorithms: the model-based DualModel and the data-driven LILA algorithm. By combining different methodological approaches, they can locate leaks with varying accuracy and meet diverse requirements. Andrea Cominola and his team aim to develop an optimal tool for leak detection and localization – featuring outstanding user experience (UX/UI) and an especially efficient interface.

The software development within the iOLE framework is based on three core principles: User-friendliness, to ensure software acceptance; Automation, to guarantee practicability in continuous use; Integration, to meet the technical requirements of utilities in terms of functionality and robustness.

The project is funded by the German Federal Ministry of Education and Research (BMBF). It is also supported under the funding initiative "Digital Green Tech – Environmental Technology Meets Digitalization",which aims to develop technologies that conserve natural resources and reduce environmental pollution.