Review of Machine Learning Algorithms in Future Smart Cities

EasyChair Preprint 7920, version 2

Abstract

The science and industrial industries have taken a keen interest in the Internet of Things (IoT) in recent years, owing to its wide range of fields and applications. IoT-based solutions are increasingly being applied in crucial usage cases in the smart city ecosystem. As a result, new digital sensors, actuators, and smartphones have been created.and mobile users have made significant progress in the commercial Internet of Things (IoT), as they can now link and exchange data from a variety of devices. 1st. Previously, integrating these devices was a very difficult task. Additionally, gathering information for day-to-day administration and planning activities for the long term is important.New statistics, such as existing commuting conditions and transit occupancy of parking spaces, as well as real-time data, such as traffic jams and pollution levels, should be continuously tracked. As a result, various innovations have been used to meet various specifications. This paper present a system review of machine learning algorithm used in smart cities.

Keyphrases: IoT, Smart Cities, machine learning

@booklet{EasyChair:7920,
  author    = {Xu Hwanwg},
  title     = {Review of Machine Learning Algorithms in Future Smart Cities},
  howpublished = {EasyChair Preprint 7920},
  year      = {EasyChair, 2022}}