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.

I. Introduction

Nowadays, we are observing an explosion of the number of Internet of Things (IoT) devices spread all around the world along with an increasing demand of efficient cutting-edge pervasive services and applications. In this context, Gartner aforesaid that the number of connected IoT devices will reach 20.4 billion [1] by 2020. Therefore, the emerging business perspectives coming from IoT are pushing private, public, and hybrid Cloud providers to integrate their systems with IoT devices equipped with sensors and actuators in order to provide together with the traditional Infrastructure, Platform and Software-as-a-Service (IaaS, PaaS, SaaS) even a new type of service level, that is called IoT-as-a-Service (IoTaaS). At the same time, with the advent of IoT the ongoing evolution of Cloud Computing has led to a drastic change in application design, deployment and delivery. Therefore, the need of efficient services and applications has pushed ICT operators to move part of their services from the "central" Cloud data centers into an intermediate layer, closer to users, defined as Edge. In this regard, Gartner also predicted that around 50% of generated sensing data will be processed outside of traditional Cloud data centers in an Edge layer by 2022 [2].