January 2023

Written by Guest Editor Qi Hong Lai

It has been a pleasure to organise the Special Issue on Data Analytics on Smart Cities – Part 1 published in November 2022, and now Part 2 for the January 2023 IEEE Smart Cities eNewsletter. Needless to say, data analytics for smart cities is very important, as reported in many publications. As part of my work, I have co-authored Smart Energy for Transportation and Health in a Smart City published by Wiley and IEEE Press in December 2022 and Smart grids and big data analytics for smart cities published by Springer in November 2020.

Written by Neethu Elizabeth Simon and Samantha Coyle

Smart cities need smart security solutions to keep assets and the public safe and secure. Surveillance cameras are installed across various parts of smart cities to ensure the safety of everyone as well as their surrounding environment. With the advent of the Internet of Things (IoT) combined with advancements in computer vision (CV) and AI/ML, security-as-a-service solutions are becoming more important in enhancing safety in a smart city.

Written by Pao-Ann Hsiung, Sapdo Utomo, John A, Adarsh Rouniyar, Hsiu-Chun Hsu, GuoHao Jiang, Chang ChunHao, and Tang Kai Chun

The growth of the AI model is not commensurate with public confidence. Some AI models contain bias or discrimination, which can be detrimental to some decision-making processes or populations. Researchers are currently attempting to tackle issues with credibility. Smart cities and artificial intelligence have been intertwined for many years, but smart citizens are concerned about the system's privacy protections. Therefore, if a system's credibility cannot be enhanced, it is a problem.

Written by Miltiadis “Miltos” Alamaniotis

The smart cities vision entails the continuous collection of data and subsequent utilization of information that is communicated in every possible direction. Its implementation requires the extensive use of sensors, information and decision-making technologies. The development and deployment of smart city technologies will benefit several aspects of residents’ daily lives. Amongst them, security is a preeminent component that will only be enhanced in smart cities. A crucial component of the overall city security architecture is that of nuclear security, which refers to the detection, identification, and localization of nuclear materials that may be used in terrorist activities. This article explores the potency of data analytics as a means for implementing smart nuclear security within the vision of smart cities.

Written by Pao-Ann Hsiung, John A, Sapdo Utomo and Adarsh Rouniyar

The enormous advancements in learning techniques over the years in the field of federated learning have made it possible to collaborate in a distributed way and to provide promising solutions with machine learning without the need to share data. Continuous improvements toward building a better model and increasing accuracy and communication between clients have in turn enabled better aggregation and increased communication rounds in the global model, resulting in an overall decrease in the consumption of energy.