Real-time water quality sensors installed at wild swimming locations
Real-time water quality sensors are being deployed at wild swimming locations and beaches across southern England. This initiative aims to provide swimmers with immediate information about potential health risks associated with polluted water.
The rollout follows a successful pilot study at Warleigh Weir near Bath, where an AI-based system demonstrated an impressive 87% accuracy rate in predicting high bacterial levels. This breakthrough showcases the potential of IoT and AI technologies in revolutionising water quality management.
Wessex Water is spearheading the implementation, installing advanced sensors at three freshwater sites in Dorset, Somerset, and Hampshire, as well as two coastal locations in Bournemouth. Concurrently, Southern Water is testing an alternative monitoring approach at Tankerton in Kent and Langstone Harbour in Hampshire, with plans to expand to Hayling Island.
The need for such innovative solutions stems from the limitations of current water quality monitoring practices. These limitations have come under increased scrutiny after rowers fell sick from suspected E. coli infection and the news that all water firms in England and Wales are now under investigation for sewage spills.
David Black, Chief Executive of the UK’s water and sewage regulator Ofwat, said:
“The fact that Ofwat now has enforcement cases with all 11 of the wastewater companies in England and Wales demonstrates how concerned we are about the sector’s environmental performance. Where we find that companies have breached their obligations, we will continue to act – over recent years, we have imposed penalties and payments of over £300 million on water and wastewater companies.
This is the largest and most complex investigation Ofwat has undertaken. However, Ofwat is committed to concluding these cases as quickly as possible, so that the sector can focus on delivering the £88bn expenditure PR24 will unlock to deliver cleaner rivers and seas. As part of this package of investment £10bn is earmarked to tackle storm overflows with a target to reduce spills from storm overflows by 44%.”
While regulations require water companies and environmental regulators to test for pollution markers, there is no mandate to check for harmful faecal bacteria like E. coli and intestinal enterococci, except at designated bathing sites. Furthermore, traditional water sample analysis often results in week-long delays, making it difficult to assess immediate risks from sewage or agricultural runoff.
The integration of IoT sensors aligns with the requirements of the Environment Act 2021, which mandates water companies to install such devices upstream and downstream of storm overflow and wastewater treatment discharges.
An IoT-powered system developed by UK-based startup UnifAI Technology takes a novel approach to water quality monitoring. Instead of directly measuring bacteria, it uses AI to infer high levels of E. coli or enterococci by analysing data from real-time sensors placed upstream. These sensors monitor various parameters, including pH, temperature, turbidity, dissolved oxygen, and ammonia levels.
The AI system undergoes a six-month training period, during which it learns to correlate bacteria levels with sensor data patterns. Once operational, the system provides public alerts on water quality every 30 minutes through a mobile app, signalling potential high bacteria levels.
Wessex Water plans to expand this IoT-driven technology to additional swimming spots, including Farleigh Hungerford, Fordingbridge, and Poole Park lagoon, along with Bournemouth and Boscombe piers. Real-time alerts for these locations are expected by 2025. The company is also in talks with landowners and river users at 20 sites across south-west England for further installations.
The widespread adoption of these IoT sensors and AI technologies promises to offer valuable insights into how storm overflow discharges and other factors influence water quality. There’s even the suggestion it could lead to the creation of a “digital twin” of river systems, enabling more comprehensive monitoring and analysis.
Southern Water is also exploring the application of UnifAI’s machine learning models to coastal water data. This research involves using algorithms to estimate bacteria levels based on light scattering, though the technology is still in the development phase and not yet available to the public.
While environmental groups like River Action UK support the introduction of real-time pollution monitoring, they emphasise that it should not detract from addressing the root causes of pollution. River Action advocates for stronger enforcement of pollution laws to drive investment in maintaining and upgrading sewage treatment facilities.
In the meantime, the deployment of these IoT-enabled water quality monitoring systems will help to empower swimmers with real-time information to improve their safety. The sensors will also provide vital data to help with the long-term improvement of water management.
(Image Credit: Adrian Pingstone)
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