Skip to main content
SpringerLink
Log in

Big Data Analytics for Smart Urban Systems

  • Book
  • © 2023

Overview

Authors:
  1. Saeid Pourroostaei Ardakani

    1. School of Computer Science, University of Lincoln, Lincoln, UK

    View author publications

    You can also search for this author in PubMed   Google Scholar

  2. Ali Cheshmehzangi

    1. Department of Architecture, Qingdao City University, Qingdao, China

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Introduces data analysis challenges and opportunities in smart urban systems
  • Describes the keys of machine learning solution design for urban sustainability applications
  • Discusses the capacities of the state-of-the-art Big data analytic approaches for urban smartness and sustainability

Part of the book series: Urban Sustainability (US)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book USD 139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (8 chapters)

  1. Front Matter

    Pages i-xix
    Download chapter PDF

  2. Big Data Analytics: An Introduction to Their Applications for Smart Urban Systems

    • Saeid Pourroostaei Ardakani, Ali Cheshmehzangi
    Pages 1-21

  3. Stock Market Prediction During COVID-19 Pandemic: A Time-Series Big Data Analysis Method

    • Saeid Pourroostaei Ardakani, Ali Cheshmehzangi
    Pages 23-39

  4. A Big Data Solution to Predict Cryptocurrency Market Trends: A Time-Series Machine Learning  Approach

    • Saeid Pourroostaei Ardakani, Ali Cheshmehzangi
    Pages 41-54

  5. Big Data Analytics for Credit Risk Prediction: Machine Learning Techniques  and Data Processing Approaches

    • Saeid Pourroostaei Ardakani, Ali Cheshmehzangi
    Pages 55-66

  6. Worldwide Mobility Trends and the COVID-19 Pandemic: A Federated Regression Analysis During the pandemic’s Early Stage

    • Saeid Pourroostaei Ardakani, Ali Cheshmehzangi
    Pages 67-79

  7. Adaptive Feature Selection for Google App Rating in Smart Urban Management: A Big Data Analysis Approach

    • Saeid Pourroostaei Ardakani, Ali Cheshmehzangi
    Pages 81-96

  8. Improve the Daily Societal Operations Using Credit Fraud Detection: A Big Data Classification Solution

    • Saeid Pourroostaei Ardakani, Ali Cheshmehzangi
    Pages 97-110

  9. Moving Forward with Big Data Analytics and Smartness

    • Saeid Pourroostaei Ardakani, Ali Cheshmehzangi
    Pages 111-126

  10. Back Matter

    Pages 127-131
    Download chapter PDF
Back to top

Keywords

About this book

Big Data Analytics for Smart Urban Systems aims to introduce Big data solutions for urban sustainability smart applications, particularly for smart urban systems. It focuses on intelligent big data which takes the benefits of machine learning to analyse large and rapidly changing datasets in smart urban systems. The state-of-the-art Big data analytics applications are presented and discussed to highlight the feasibility of big data and machine learning solutions to enhance smart urban systems, smart operations, urban management, and urban governance. The key benefits of this book are, (1) to introduce the principles of machine learning-enabled big data analysis in smart urban systems, (2) to present the state-of-the-art data analysis solutions in smart management and operations, and (3) to understand the principles of big data analytics for smart cities and communities. 



Endorsements


‘Over the many years of collaboration between academia and industry, we noticed the common language is ‘big data’; with that, we have developed novel ideas to bridge the gaps and help promote innovation, technologies, and science’.
- Tian Tang, Independent Researcher, China

 ‘Big Data Analytics is a fascinating research area, particularly for cities and city transformations. This book is valuable to those who think vigorously and aim to act ahead’.
- Li Xie, Independent Researcher, China


‘For urban critiques, knowledge trains aspiring opportunities toward outstanding manifestations. Smartness has evolved or/ advanced rambunctious & embracing realities along (with) novel directions and nurturing integrated city knowledge’.
- Aaron Golden, SELECT Consultants, UK


Authors and Affiliations

  • School of Computer Science, University of Lincoln, Lincoln, UK

    Saeid Pourroostaei Ardakani

  • Department of Architecture, Qingdao City University, Qingdao, China

    Ali Cheshmehzangi

About the authors

Saeid POURROOSTAEI ARDAKANI currently works as a Senior Lecturer in Computer Science at the University of Lincoln, UK. He is also an associated academic member of Lincoln Centre for Autonomous Systems (L-CAS), and has formerly worked at the University of Nottingham (UNNC) and Allameh Tabatabai University (ATU) as an Assistant Professor in Computer Science, member of the Next Generation Internet of Everything Laboratory (NGIoE) and Artificial Intelligent Optimisation Research group, and head of ATU-ICT center. He received his PhD in Computer Science from the University of Bath focusing on data aggregation routing in Wireless Sensor Networks. Saeid’s research and teaching expertise centres on smart and adaptive computing and/or communication solutions to build collaborative/federated (sensory/feedback)systems in Internet of Things (IoT) applications and cloud environments. He is also interested in (ML-enabled) Big Data processing and analysis applications. Saeid has published more than 60 scholarly articles in reputed international journals and peer-reviewed conferences.


Ali CHESHMEHZANGI is the World’s top 2% field leader, recognised by Stanford University. He has recently taken a senior leadership and management role at Qingdao City University (QCU), where he is a Professor in Urban Planning, Director of the Center for Innovation in Teaching, Learning, and Research, and Advisor to the school’s international communications. Over 11 years at his previous institute, Ali was a Full Professor in Architecture and Urban Design, Head of the Department of Architecture and Built Environment, Founding Director of the Urban Innovation Lab, Director of Center for Sustainable Energy Technologies, and Director of Digital Design Lab. He was Visiting Professor and now Research Associate of the Network for Education and Research on Peace and Sustainability (NERPS) at Hiroshima University, Japan. Ali is globally known for his research on ‘urban sustainability’. So far, Ali has published over 300 journal papers, articles, conference papers, book chapters, and reports. To date, he has 15 other published books. 

Bibliographic Information

  • Book Title: Big Data Analytics for Smart Urban Systems

  • Authors: Saeid Pourroostaei Ardakani, Ali Cheshmehzangi

  • Series Title: Urban Sustainability

  • DOI: https://doi.org/10.1007/978-981-99-5543-5

  • Publisher: Springer Singapore

  • eBook Packages: Social Sciences, Social Sciences (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023

  • Hardcover ISBN: 978-981-99-5542-8Published: 28 September 2023

  • Softcover ISBN: 978-981-99-5545-9Due: 29 October 2023

  • eBook ISBN: 978-981-99-5543-5Published: 27 September 2023

  • Series ISSN: 2731-6483

  • Series E-ISSN: 2731-6491

  • Edition Number: 1

  • Number of Pages: XIX, 131

  • Number of Illustrations: 3 b/w illustrations, 59 illustrations in colour

  • Topics: Sustainable Development, Statistics, general, Human Geography

Publish with us

Policies and ethics

Back to top

Search

Navigation