When we talk about "water sustainability", experts use some fundamental indicators. For us, the most important is the resilience of their infrastructures, i.e. how prepared they are for adverse situations, and the efficiency of their processes, measured as the number of resources to be invested in meeting a specific demand. AI plays a fundamental role in these processes.
The effects of climate change on temperatures and drought are becoming increasingly evident. This, coupled with a growing population and increasingly extensive use of water resources, makes the debate on water sustainability increasingly relevant.
When we talk about "water sustainability", experts use some key indicators. For us, the most important are the resilience of their infrastructures, i.e. how well prepared they are for adverse situations, and the efficiency of their processes measured by the amount of resources to be invested in meeting water supply and demand.
A few days ago we heard that a historic drought in Italy has forced the country to impose restrictions on the use of drinking n some cities. Could this have been avoided with more resilient infrastructures or more efficient processes? The answer is yes, but the challenge is how to raise those levels of resilience and efficiency required by the current socio-climatic context. To this end, all eyes are on the modernisation and digitisation of water management infrastructures.
The big challenge when digitizing water infrastructure has been the lack of visibility of their operations starting with consumption measurement. For many utilities, the current meter fleet still contains many legacy meters, which only allow very basic parameters to be read manually. Efforts are being made in all regions of Spain to accelerate the replacement by Smart Meters, that can measure many more parameters and on a continuous basis.
The installation of Smart Meters has a direct impact on sustainability as it allows:
1. Identify in real time any excessive use and change consumption habits or limit them in order to eliminate them in the future. 2. Detect the early signs of a leak and thus avoid unnecessary losses and reduce the risk of flooding. 3. Optimization of water storage and water distribution, to meet the needs of water consumptions. 4. Better monitoring of unregistered water (fraud).
However, the installation of Smart Meters is not without its complexities for water operators. Millions of smart meters implies the management of billions of data and adds greater complexity to water managemente and maintenance that includes connectivity management, software upgrades, and other aspects that utilities are not fully prepared for.
Barbara the Industrial Edge Platform for Smart Water, offers a solution that enables multi-manufacturer and multi-technology Smart Meters to be centrally managed, saving hundreds of hours of maintenance teams' time and maximising the use of smart meters. All this through a series of functionalities such as user management, device provisioning and lifecycle management, software configuration and connectivity, fleet performance analysis, identification of discrepancies and alerts, and remote firmware upgrades, among others.
The monitoring and operation processes of a water network have traditionally been carried out with the help of sensors and SCADAs, but with a strong dependency on operators to analyse and respond to the data. With the evolution and democratisation of artificial intelligence now it is possible to analyse data more massively very quicky, including historic data.
Artificial Intelligence at the Edge can help in adjusting quality-related chemical processes in sewage treatment plants, resulting in important cost savings in the usage of chemicals and energy consumption.
ACCIONA managed to reduce in 250.000 € per plant with a better usage of chemicals by deploying AI in the Edge. The great challenge from the technological perspective was based on the connectivity of a protocol as specific as OPC-UA. It was essential to be able to perform a secure and guaranteed authentication to allow it to connect to the server and, in this way, to be able to read parameters simply and in isolation from the operation so that it would not affect the normal operation of the plant.
Considering the different types of hardware available, both connectivity and sensors, there was a need for a flexible and cybersecure technology that would allow connectivity with multiple devices and ensure the security of the devices and the extracted data.