Smart water grids: solutions based on IoT and machine learning

Smart water grids (SWGs) are an emerging technology that combines the power of the Internet of Things (IoT) with advanced water management systems. These grids are designed to monitor and control water distribution in a more efficient and sustainable way, thus they are becoming increasingly important as water resources become scarcer. The key feature of SWGs is the ability to collect data in a continuum manner. In this paper, we discuss the potential benefits of the use of machine learning on IoT collected data. We also define a deep learning model to identify patterns in consumption data based on clustering. Experiments are performed on data gathered through a LoRaWAN IoT platform measuring a regional water distribution system. Thanks to this approach, we can help water utilities to adapt the distribution plan according to users' behaviours.