South East Water (SEW) is looking to suppliers for more information about market capability, trends and align innovative opportunities with existing technologies and understand how it can drive a more efficient operation through IoT, analytics and AI digital transformation.
The water company, which supplies drinking water to 2.2 million consumers and expects to have 90 % metering penetration by the end of 2018, wants to improve outcomes for customers.
SEW said it would like to explore the potential to incorporate the services and tools, from meter manufacturers, software solution providers and IoT sensor vendors into one integrated solution, and through this realize the full benefit of digitisation.
Smart water networks is a key element of the utility’s move to a more predictive and preventative operating model, creating a digital twin of assets, and using machine learning and AI tools to measure, predict and propose interventions on its system dynamically.
The objective of the trial is to have a solution that enables SEW to visualise, analyse, monitor, predict and improve the real-time performance of its water network. Integrating relevant internal and external data sources into one platform by also combining new sensors and AMI meters, the solution would enable users to correlate and analyse the data while providing different views and capabilities.
To better understand how this could work, and how the separate elements would be integrated to achieve this objective, SEW intends to run a 1 year trial. The trial would be used to determine whether combining the latest advancements in technology would provide sufficient efficiencies and performance improvements to justify a wider implementation for the future following a full procurement exercise.
The results of the trial will then be reviewed and used to inform leakage and metering strategy.
Interested parties should confirm their interest by obtaining further information by e-mailing This e-mail address is being protected from spambots. You need JavaScript enabled to view it for full details of the process and timescales. Expressions of interest must be submitted by 9.7.2018.
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