Inflowmatix is a spin-out company from the InfraSense Labs at the Department of Civil and Environmental Engineering of Imperial College London. Inflowmatix builds upon the unique cross-disciplinary expertise from sensing to advanced modelling and optimization and the active research collaborations with water utilities and IT system integrators.

Inflowmatix creates innovative and customer tailored solutions for the steady-state, resilient and energy efficient operation of water supply networks by continuously monitoring and analyzing the fluid dynamics in complex networks. This allows operators to continuously gain unique insight and proactively optimize the dynamic network performance in order to extend the service life of infrastructure assets. Our expertise in modelling the steady and unsteady-state hydraulics of water distribution networks, combined with knowledge and experience in the design and implementation of embedded electronic systems, yield compelling returns on investment for our customers.

Their Technology
Background Water utilities are beginning to recognize the importance of monitoring and controlling the dynamic hydraulic conditions in complex water supply networks. Various technologies are emerging that allow operators to capture extreme but rare pressure transient events. However, simply capturing such extreme pressure transient events tends to cause data overload and anxiety. “Data rich, information poor” is an often quoted phrase. Inflowmatix uses high-resolution data to answer critical questions with regards to the dynamic flow conditions in order to support the prioritisation of network interventions, the management of risk and the implementation of hydraulically calm networks.

InflowSenseTM – What does it do?

Our InflowSenseTM monitoring and analytical technology enables the water companies to transform data into operational intelligence by continuously measuring and analysing the dynamic hydraulic performance and health of water supply networks. We are able to identify areas that have been subject to historic and current pressure-induced stress thus detecting and diagnosing even subtle changes in assets performance that may increase the probability of failures.