Join us on Wednesday, 30th April, with Northumbrian Water and Cognizant, for the River Deep Mountain AI (RDMAI) Demo Day.

Alongside project partners including ADAS, WRc Group, Wessex Water, Xylem, Anglian Water, Welsh Water, Northern Ireland Water, South West Water, Stream, The Rivers Trust, Google, and Uisce Éireann, NWG is leading on an Ofwat-funded project, RDMAI, that is working to develop open-source, scalable, digital models that will analyse new and existing data inputs that unlock new insights to tackle waterbody pollution.

As part of the project, Spring is hosting a webinar, developed alongside Cognizant, where the project team will share progress updates, current status, and future steps. There will also be time reserved for an engaging Q&A session, during which your feedback will be highly valued.

Purpose and format of the session

  • A conference-style demonstration of our work to date, highlighting learning milestones for Phase 2. The session is open for all.
  • The key purpose of the day is to share the learnings, inviting stakeholders to see RDMAI’s progress, ask questions and provide feedback.

Expected outcomes

The demo day aims to achieve the following outcomes:

  • Stakeholder engagement and representation: Foster meaningful discussions with a diverse audience
  • Validation of progress: Demonstrate advancements in key themes and get validation from stakeholders.
  • Actionable feedback: Gather input to refine models and approaches, ensuring continued alignment with stakeholder needs.
  • Momentum building for adoption: Strengthen awareness and ownership among stakeholders to lay the foundation for adoption after the project concludes.

Further information on RDMAI:

The UK’s Rivers are under pressure. Right now, only 14% of English rivers meet the standards for good ecological health. Climate change, pollution, floods, and droughts are accelerating the crisis. The rivers are facing depleting oxygen levels, loss of biodiversity, and pollution events. Rivers suffer from diffuse pollution, nutrient overload, and harmful bacteria —threatening both ecosystems and communities.

What if we could harness AI to change this?

River Deep Mountain AI is working to develop open-source, scalable AI/ML models to uncover pollution patterns and unlock actionable insights for protecting waterbodies. Data on waterbody health is scarce, so the RDMAI team is working to squeeze as much actionable information out of existing data as possible. By integrating data from various sources, including environmental sensors, satellite imagery and citizen science, the project aims to bridge the data gaps in waterbody health and empower better, faster, and more effective interventions.

 

We look forward to your participation and the valuable insights you’ll bring to the discussion.

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