Siemens has introduced a service that provides UK water utilities with the real-time water quality data and insights they need to get ahead of issues in drinking water networks and improve maintenance regimes.
The new Water Quality Analytics as a Service (WQAaaS) simplifies and derisks the process of bringing insight directly into water company operations, accelerating the pace of digital transformation and empowering companies to push the standard against the demanding performance commitments that will be set for AMP8, the eighth asset management period regulated by Ofwat.
The solution provides network operators with the installation and management of sensors, data connectivity, data visualisation, integration into existing data sources, and analytical insights from the treatment works to the customer’s tap.
The transformative analytics modules are deployed in a secure cloud platform and enable water utility companies to review the estimated travel time throughout the network, helping operators manage the risk of bacterial growth in water that’s been in the system for extended periods, optimising water safety processes.
The solution will also reduce the risk of discolouration complaints and the cost of flushing programmes by quantifying the movement of material through the network. This assists with highlighting areas of elevated risk of discolouration of water supply and with guiding intervention works in the right areas to get the best return on investment for those interventions.
WQAaaS can also reshape how water providers approach maintenance. Cloud-based analytics modules will inform the scheduling of service reservoir cleaning to be driven by performance and accumulation of material, reducing both operational costs and risk. The technology can also improve resilience and response to incidents by combining real-time data with District Metered Area (DMA) level simulation of water age and chlorine levels.
In the long run, this can allow users to review the relationship between leakage events and changes in water quality parameters to inform potential changes in network management.