Data Management in Smart Cities Collected from Internet of Things

EasyChair Preprint 10422

Abstract

The continuous growth of the Internet of Things (IoT) has furled development of bright cities, where interconnected devices and sensors generate vast amounts of data. Effective data management is crucial for harnessing the potential of IoT in smart city contexts. This research paper explores the challenges and strategies related to data management in IoT-enabled smart cities. It delves into the various aspects of data management, including data collection, storage, processing, integration, and analysis. The paper examines the unique characteristics of IoT data, such as its volume, velocity, variety, and veracity, which pose significant challenges for traditional data management approaches. Additionally, the paper investigates the role of edge computing, cloud computing, and distributed architectures in facilitating efficient data management in IoT smart cities. Furthermore, it explores data governance frameworks, privacy concerns, and security considerations associated with managing IoT generated data. The research draws insights from existing literature, industry practices, and case studies to provide a comprehensive understanding of the current state, emerging trends, and future directions of data management in IoT smart cities. The findings of this research contribute to the development of strategies and best practices for managing and leveraging the wealth of data generated by IoT devices in the context of smart cities.

Keyphrases: Internet of Things, Smart Cities, data management

@booklet{EasyChair:10422,
  author    = {Surya Chauhan and Sunil Saini and Suyash Mohan Saxena and Neha Bagwari},
  title     = {Data Management in Smart Cities Collected from Internet of Things},
  howpublished = {EasyChair Preprint 10422},
  year      = {EasyChair, 2023}}