Water quality is a hot topic. AI can help.

In the UK concerns about our water ways range from the very sensational headlines associated with the collapse of Thames Water to longer standing environmental stewardship concerns such as the considerations affecting Poole Harbour and the Wye valley. The case of Poole Harbour is informative. Poole Harbour is a site of special scientific interest. In 2015, the World Wide Fund for Nature, the Angling Trust and Fish Legal undertook a Judicial Review against the Secretary of State for Department, Environment, Food and Rural Affairs (DEFRA) and the Environment Agency based on perceived non-consideration of Water protection Zones to tackle diffuse water pollution in Poole Harbor.The Secretary of State is now bound to act to reduce nitrate leaching under a Consent Order. To this end DEFRA, representing the UK government, is mandated to demonstrate a reduction of nitrate and phosphate pollution in order to meet the requirements of the European commission. Given that the farming community is held accountable for two thirds of the nitrate leachates, the Secretary of State is de facto required to work directly with farmers to develop nitrate leaching management solutions.

At bigspark we know that AI can provide the data and decision making capability and given our data for good and AI for good value system we are introducing a multi-discipline team of AI advisors, Data engineers, data scientists, research organisations and agronomy specialists to interested clients. We have designed a three step program:

First, our Responsible AI advisors are legally trained, and so have familiarity with the regulatory requirements placed on stakeholders. As an example Water quality monitoring in the jurisdiction of England and Wales must comply with (i) Nitrate Pollution Prevention Regulations 2015, (ii) The prevention and reduction of diffuse pollution agriculture regulation 2018, and (iii) Water Resources (Control of Pollution) (Silage, Slurry and Agricultural Fuel Oil) (England) Regulations 2010 (SSAFO). Legislation makes clear what factors are to be measured and reported. As but one example the Nitrate pollution prevention regulation requires the concentration of nitrates in the water to remain at or less than 50 mg/l.

Second, by working in partnership with Nottingham Trent University we are actively investing in developing cognitive edge devices. Devices support sensor hosting and transmission of relevant data streams back to the source. Our architecture enables off line and on line scenarios to ensure we cater for a variety of use cases. By running devices with computer vision raw sensor data capture can be correlated with impacts on aquatic and marine life to migrate towards outcome centric monitoring and management of the environment.

Third we are using Artificial Intelligence (AI) to revolutionize the water quality monitoring services offering innovative, cost-effective, and efficient solutions. AI enables real time monitoring and early warning systems to be deployed alongside continuous data collection and analysis. Sampling rates can be adapted through use of the platform which can allows for the swift identification of nitrates or phosphates as one example, or. harmful bacteria such as E.Coli as another. The service can facilitate rapid responses to potential contamination events. Better yet, AI systems can predict events like sewage overflows or agricultural runoff, enabling proactive measures to protect water resources when integrated with other services, using relatively low cost sensors. These new AI based methods and extended data capture methods can be used to assess flow and AI models make it possible to leverage vast datasets to improve accuracy and predict needs. We provide our clients with private and secure data capture first so that our clients are able to truly understand their impact in privacy first such that they can then prepare to optimize their resource allocation for water management with agencies like the EA or European commission when ready.

The approach we’re introducing not only delivers remarkably new data sets of information for reducing pollution but also offer significant cost benefits by leveraging AI to enhance efficiency and reduce expenses. There are key cost advantage options delivered by use low cost sensors, predictive maintenance and more effective nitrogen application but perhaps most importantly, by promoting responsible Environmmental management methods grounded in data and analysis, bigspark provides neutral, factual evidence centres that enable all stakeholders can use. Farmers, Water companies, Anglers, etc. can all examine the evidence and focus their efforts, not on debating the facts and the source, but on improving our environment.

Community collaboration enhanced by AI insight is key to water quality monitoring success.