• Waste Water Network

    Use Weather Forecasts and Machine Learning Technology to Visualise, Categorise and Optimise Waste Water Network performance and reduce CSOs

The StormHarvester Waste Water Networks Product Suite use Weather Forecasts and Machine Learning Technology to Visualise, Categorise and Optimise Waste Water Network Performance and reduce Combined Sewer Overflow events.

Click below to book a demo today or find out more by reading our Waste Water Network Case Study.

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Read our Waste Water Network Case Study

Download our Waste Water Network Brochure

96% accuracy on CSO predictions
30% reduction on CSO discharge
8 times cheaper than Capital Upgrades

The StormHarvester Waste Water Networks Product Suite.

Network Analysis.

Instant visibility on overall network performance

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Real-time Predictions.

All the benefits of network analysis and…

Real-time warnings for CSO spillages and pipe blockages

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Automated Control.

All the benefits of network analysis, live alerts and……

Automated control of waste water networks in wet weather conditions to reduce combined sewer overflows

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Energy Reduction.

All the benefits of Network Analysis, Live Alerts, Automated Control and……

Waste Water Pumping Station control to optimise performance and reduce Energy Consumption

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Case Study.

StormHarvester and Northumbrian Water have worked together since early 2018 to analyse pumping chambers in Newcastle-Upon-Tyne in Northern England.

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Machine Learning.

StormHarvester’s machine learning software learns the network performance based from historic and real time data.  Our algorithms are then used along with radar rainfall forecasts to predict network performance and where necessary take pre-emptive action to reduce pollution incidents and identify network failures in real time.

Seamless Integration with SCADA systems
Easy reporting and compliance
No additional sensors or flow meters required

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