Digital Water Approach for Smarter Water Management in Cities with Interconnected Infrastructure

Water management in cities has come a long way since the inception of early infrastructure long time ago. The modern water systems provide safe and reliable service via effective supply of clean water and collection, disposal and recycling of wastewater. However, the increasing pressures arising from the climate change, population growth and urbanisation are posing further challenges that need to be addressed in the urban environment. The advancement of new technologies such as latest artificial intelligence and machine learning methods, intelligent sensors and actuators linked via internet of things and fast 5G communication networks (to name the few) provide an opportunity to manage water in cities in a fundamentally different way that is more sustainable and resilient but also less impactful on other infrastructure systems.

The talk will start by defining what is meant by a smart water system in the context of a smart city. This will be followed by the presentation of several advanced type technologies and solutions that have been developed for the improved management of water and wastewater in urban environment. This includes new data analytics type technology for the automated detection and location of pipe bursts/leaks, equipment failures and other failure events in a water distribution system. This technology detects failure events in these system by processing pressure, flow and other data in near real-time by using artificial intelligence and other methods. In addition to saving water, energy and other resources this technology has the potential to reduce or, in some cases, prevent the negative impact of WDS failures on other infrastructure systems (e.g. impact on a transport system via major road closure following a pipe burst).

Another example that will be presented is the new technology for automated asset condition assessment of sewers. This technology, currently being commercialised,  processes standard CCTV data by using image processing and machine learning techniques to identify and classify structural and other faults in these pipes. The increased reliability and consistency of detection of these faults has the potential to reduce or remove the negative impact of related sewer failures on other critical urban infrastructure systems, e.g. impact on traffic or energy systems due to urban flooding and/or pollution that may occur as a result of non-detection.  A number of other smart water technologies and solutions will be presented. Most of these were developed in collaboration with various water utilities hence are of direct relevance to engineering practice. The talk will end with the key message that digital water approach has a huge potential to improve things in the water and other sectors.