# Smart Energy Meters for Smart Grids, an Internet of Things Perspective
## 1 Introduction
\begin{table}
\begin{tabular}{c p{227.6 pt}} \hline \hline
**Reference** & **Comments** \\ \hline
[13] & Optimized random forest algorithm implementation for data analytics in smart meters \\ \hline
[14] & An extensive review of different techniques implemented on smart meter data for home and battery management system \\ \hline
[15] & Implementation of deep learning on smart meter data to gain insights into load forecasting \\ \hline
[16] & A statistical model that determines the characteristics of households who would benefit or suffer from a time-of-use tariff. \\ \hline
[17] & Finding energy consumption patterns using smart meter data through machine learning \\ \hline
[18] & Discusses the evolution of energy meters from the past \\ \hline
[19] & A case study explaining the impact of battery storage on energy consumption using smart meter data \\ \hline
[20] & Discussion of smart meter hardware, communications, and security in terms of its contribution to the smart grid \\ \hline
[21] & Explanation of different types of non-technical losses that exist in the grid and how smart meters can help in removing them \\ \hline
[22] & Focuses on compression techniques of big data available from smart meters \\ \hline
[23] & Explains different types of smart meter communication technologies to realize smart metering connectivity \\ \hline
[24] & Use case discussion as to how residents of UK are responding to smart energy via digital comparison tools \\ \hline
[25] & Discussed three reliability prediction methods to analyze smart meter data to predict life of the meter \\ \hline
[26] & Fosters the understanding and adaption of modern deep learning methods to solve the challenges regarding energy supply \\ \hline
[27] & Discussion of challenges and opportunities of smart meters in smart grids and homes \\ \hline
[28] & LoRaWAN technology explored in detail in terms of capacity limits \\ \hline
[29] & Comprehensive review on the existing and future communication infrastructures \\ \hline
[30] & Features of IoT protocols reviewed comprehensively for smart meters and smart grids in general \\ \hline
[31] & Investigates emerging tech such as cognitive radio networks in 5G for reliable communication in smart grids \\ \hline
[32] & Review of security issues and their solutions regarding cyber–physical systems of AMI \\ \hline
[33] & Review of AMI technology for smart meters discussing different varieties of control, facilities, and features \\ \hline
[34] & Discussion on various elements of smart metering, current state of the technologies, AMI, and meter data flow with respect to smart grid \\ \hline
[35] & Thorough review of smart meter data classification of electricity consumption \\ \hline
[36] & Data analytics review paper analyzed from customer-centric perspective by discussing their technological foundations and impact \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Overview of different reviews and applications of smart meter. These factors warrant an overview of the advancement of the underlying technology vis-a-vis the current and the prospective applications that are or can be enabled by such an advance. While there are numerous papers that review the smart meters, measurement technologies, edge applications for smart metering, communication protocols and interfaces, software stacks, and computation hardware for IoT and, to some extent, for smart meters, a holistic review that sets each of the components in the context of smart metering for smart energy is lacking, to the best of our knowledge. With this review, the intention is to bridge this gap. In this review, an overview of the architectural composition of the different solutions for the smart meter reported in the literature is presented. The main aim is to follow the evolution of the functionality and the capability of the smart meter, predict the trajectory for future designs and, most essentially, point out the unexplored opportunities presented by the advancement of the underlying technologies.