Development of a Smart Metering Microservice Based on Fast Fourier Transform (FFT) for Edge/Internet of Things Environments

In recent years, great attention has been given to new Internet of Things (IoT) technologies. The IoT concept is nowadays intrinsic to traditional products and services. With its rapid development, more and more small smart devices are connected over the Internet in order to monitor, collect and exchange data in real-time to provide smart IoT-as-a-Services (IoTaaS). A few years ago, IoT devices exclusively sent data to a centralized Cloud data center; today it is possible to perform "on board" processing tasks at the Edge of the network and subsequently share or use the obtained results closer to users. This paper, focusing on a smart grid scenario, investigates the possibility of creating an IoTaaS for smart metering, including a microservice for IoT devices capable of acquiring and processing electrical data using the Fast Fourier Transform (FFT) algorithm. In particular, we experimentally use the smart metering IoTaaS running on a Raspberry Pi 3 device to perform a harmonic analysis of a frequency signal of the domestic electrical grid in order to characterize the non-linear loads associated to the electronic devices (e.g., smart TV, computers, etc) with the purpose of monitoring their status and preventing possible malfunctions and faults.