AI:Liner

The core of the project is building an interoperable end-to-end asset management system that doesn't just find problems faster (with up to 95 % accuracy) but also makes strategic decisions on when and where to repair. Ultimately, AI:Liner champions the long-term use of cost-effective and greener liner technology over traditional excavation, cutting rehabilitation costs by up to €8 billion annually and accelerating the water sector’s digital and green transition.

The AI:Liner project's main activities focus on developing and testing six pioneering digital solutions to transform sewer management. Key technological developments include remote sensing (S1), autonomous UAVs for inspection (S2), and acoustic sensors (S3) for real-time monitoring and defect detection. Concurrently, the project builds advanced AI models for automatic defect recognition (S4), risk-based prioritisation (S5), and long-term investment planning impact analysis (S6). These efforts aim for significant results, such as reaching up to 95 % accuracy in identifying maintenance needs and enhancing knowledge on liner durability (K1), ultimately working to reduce health and safety risks for workers (K6) and ensure the open accessibility of non-sensitive research outputs.