Collaborative innovation venture River Deep Mountain AI (RDMAI) has introduced the open-source launch of a set of synthetic intelligence and machine studying (AI/ML) fashions that it says are set to rework the way in which water high quality information is collected and used.
Funded by Ofwat’s Water Breakthrough Problem and led by Northumbrian Water, with Spring Innovation because the knowledge-sharing accomplice, RDMAI is a cross-sector initiative constructing open-source, scalable AI instruments to deal with waterbody air pollution and enhance river well being. Information from a spread of sources, together with citizen science and satellites, has been used to construct the fashions.
The discharge of AI/ML and remote-sensing fashions on the open-source platform GitHub is the venture’s first main milestone, following completion of the event and preliminary testing phases. All through this era, the venture crew collated datasets from inside and out of doors the sector, run experiments with AI/ML fashions and held co-creation classes with companions and stakeholders.
The ensuing fashions and datasets goal to assist:
- River circulate predictions
- Air pollution supply monitoring
- Air pollution hotspot mapping
Suggestions is invited at this stage to assist refine and improve the fashions because the venture progresses.
The UK’s water setting is underneath stress from inhabitants development, local weather change, air pollution from a number of sources and nutrient overload. Simply 14% of English rivers are assembly Water Framework Directive requirements for good ecological standing.
Launched in July 2024, River Deep Mountain AI goals to deal with this problem by creating open-source, scalable AI/ML fashions to uncover air pollution patterns and unlock actionable insights for safeguarding waterbodies.
Northumbrian Water’s venture companions are: ADAS, Anglian Water, Cognizant, Northern Eire Water, South West Water, Stream, The Rivers Belief, Google, WRc, Wessex Water and Xylem.
George Gerring, venture lead, Northumbrian Water, mentioned, “We’ve constructed a set of capabilities that use synthetic intelligence, machine studying, generative AI and distant sensing to know and predict totally different variables impacting waterbodies well being.
“The open-source launch of those fashions on GitHub means they’re out there for residents, researchers, water organisations and NGOs to make use of. Any suggestions on the early releases will assist us refine and construct on what we’ve achieved thus far.”
Angela MacOscar, head of innovation, Northumbrian Water, mentioned: “Useable information on waterbody well being is disparate and arduous to entry, which is why the RDMAI crew is working to squeeze as a lot actionable data out of current information as doable.
“By integrating information from numerous sources, together with environmental sensors, satellite tv for pc imagery and citizen science, the venture is bridging the info gaps in waterbody well being and empowering higher, sooner and simpler interventions. Open-sourcing these fashions marks a significant shift in how we collaborate to deal with environmental challenges.”
Stig Martin, international head of ocean, Cognizant, mentioned: “This venture is a testomony to the ability of analysis and improvement and daring to make use of know-how to resolve complicated, large-scale environmental issues.
“We consider in transparency and are proud that this venture is open-source, permitting everybody to see how the system is constructed and the way it generates its insights. It has been extremely rewarding to be a part of a collaboration that isn’t simply speaking about change however is actively constructing the instruments to make it occur.”
Part three of the programme, now underway, will deal with mannequin enchancment, validation in new catchments and evaluating the potential to scale throughout the UK. The refined variations of the fashions are set to be launched in November.
The GitHub web page for RDMAI may be considered at https://github.com/Cognizant-RDMAI
