Processing Smart Meter Data Using IoT, Edge Computing, and Big Data Analytics

Abstract

Smart meters have the potential for improving the accuracy of demand forecasts and the energy efficiency, also allowing for the reduction in energy consumption. Mostly the smart meter data is used for the measurement of energy usage at the consumer side that is then sent to the utility providers for billing purposes and demand planning. The Internet of Things (IoT) is used to collect the data from smart meters, and that data is used for the calculations and visualization for smart grid maintenance and future decisions. The number of smart meters is constantly increasing and so is the data from those meters. Gathering and performing analytics on such data is a hard computational task. In this study, we have highlighted the role of IoT, edge computing, and big data and analytics focusing on how to speed up the information retrieval from the smart grid data and how that information can be used for multiple purposes, not only for billing purposes. A framework for more efficiently analyzing data obtained from smart meters is presented, which utilizes edge computing and big data and analytics to process raw data to useful information.