Water sensor being installed in a river, collecting real-time data on water quality.

Artificial intelligence is transforming the fight against water pollution, with a groundbreaking pilot project in south-west England aiming to predict and prevent pollution incidents before they occur. Through the integration of AI, the picturesque seaside resort of Combe Martin in Devon is on its way to becoming a better place for swimming and recreation.

Harnessing the Power of AI for Water Quality Improvement

Cutting-edge sensors placed strategically in rivers and fields are collecting real-time data on water quality, rainfall, and soil conditions. This information is then combined with satellite imagery of local land use, enabling AI systems to predict vulnerability to pollution events, such as agricultural runoff.

A network of sensors providing real-time information on changes in water quality

The Potential of AI in Preventing Pollution

Leading computer systems company CGI and mapping experts Ordnance Survey are spearheading the artificial intelligence project. During a test run, the AI system achieved over 90% accuracy in predicting pollution incidents, highlighting its potential in water pollution prevention.

A Hope for Cleaner Beaches

Combe Martin, a renowned seaside resort, has long struggled with water quality concerns. The project aims to clean up the town’s beaches by primarily addressing pollution originating from the River Umber, which carries sewage treatment plant discharges and agricultural runoff.

Real-time Monitoring and Data Integration

Deploying approximately 50 connected sensors across the catchment area, the project collects crucial data on water, soil, and rainfall. Ordnance Survey’s expertise in integrating this information with satellite imagery enables the AI model to identify patterns, such as pollution events triggered by rainfall.

The River Umber at Combe Martin, a source of pollution entering the sea.

A Path to Effective Prevention

With the AI’s ability to predict pollution events, proactive measures can be taken to mitigate contamination risks. For instance, farmers may be advised to delay applying fertilizers when the soil is dry and heavy rain is forecasted, reducing the likelihood of runoff into waterways.

Challenges and Future Scale-Up

While the AI model has shown promise, preventing raw sewage discharge during heavy rainfall remains a complex issue. However, as the project expands, efforts will be made to tackle such challenges and scale up the initiative to benefit other parts of the UK.

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