Monitoring Water Quality

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Water Quality monitoring has been a key focus area for UnifAI. We believe we have created the most advanced and affordable water quality monitoring and risk assessment engine in the world.

 

By converging low cost sensing with AI, our solution provides an affordable real-time early warning system that provides continuous monitoring at lower cost than traditional methods.

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Our Artificial Neural Network is trained with millions of historic water quality data points. This enables us to start with a small number of sensor parameters and accurately measure a very wide range of additional parameters, including harmful bacteria such as E.Coli.

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The real time identification of events provides an early warning system for the risk based prioritisation of interventions, and once enough data has been collected the AI can learn to predict some events before they occur.

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Customers can continuously monitor for harmful bacteria using low-cost remote sensors. This helps to significantly improve the health of water, infrastructure and people. For example, identifying and alerting for sewage overflows or agricultural runoff in the natural environment, or the risk of Legionella in buildings.

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Our AI is sensor-agnostic, but we have teamed up with partners WATR and WaterSense to provide pre-integrated sensors to cover a range of use cases. Our unique "hub and spoke" approach optimises the use of multi-parameter sensors for AI training, with multiple low-cost sensors providing an instant and easy to deploy network.

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The unique value of our solution comes our use of AI to deliver a wide range of high-value parameters from lower cost, simpler sensors.

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Our Poole Harbour project is a typical example. Our AI is providing the following outputs:

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