Water distribution networks are essential to daily life, yet much of the infrastructure in use today, especially piping, was laid decades ago, maybe even centuries ago. Older pipes and infrastructure don’t align with new technologies.
You already know when they break, when seasonal weather patterns drive either a drought or a flood scenario. Fortunately, IoT and advanced materials allow cities and utilities to transition by using better rea-time data and more effective planning.
Legacy pipework
Most urban water systems were built for durability but not for smart technology integration. The United States, as an example, has more than 2.2 million miles of aging underground pipes—many of which are over 50 years old and prone to corrosion and leaks.
Real time monitoring
IoT sensors using BLE, LoRa orNB-IoT allow water utilities to monitor every stage of the water distribution process in real time, from water quality to flow rates and pressure levels. These sensors provide a comprehensive overview of network health, which is invaluable for identifying weak points and preventing major breakdowns. According to a report from Navigant Research, the use of IoT in water management is expected to save utilities up to $2 billion annually, by reducing waste, improving transparent billing efficiency and delivering better network access.
Advanced leak detection is one area where IoT sensors shine. In traditional systems, finding a leak often requires costly and disruptive digging. Now, acoustic and pressure sensors can identify even minor leaks before they escalate. For example, Sydney Water in Australia uses IoT sensors to monitor pipeline networks, helping reduce leak rates by 10% in the first year of deployment.
Building better infrastructure
Modern materials are key to integrating IoT into old networks. Pipes with built-in sensor technology are now available, often made from corrosion-resistant materials like ductile iron and composites that withstand harsher conditions than older cast iron. Smart pipes, embedded with temperature, pressure, and flow sensors, communicate directly with monitoring systems. This provides a real-time map of water flow and conditions across an entire network, even in remote or inaccessible areas.
Data and Predictive Maintenance
One of IoT’s advantages is its ability to gather massive amounts of data, which can be used to predict future issues. On the other hand, having a huge tranche of data flowing endlessly is no use either. There is a need for back end tooling to sort and prioritize the key data elements.
Machine learning can analyze the data from sensors to predict when parts of the system need to be looked at, or need repair or replacement. This approach, called predictive maintenance, saves time and resources, compared to reactive repairs.
