Call for Chapters: Leveraging IoT and Machine Learning for Smart Urban Planning

Editors

Muneer Ahmad, University of Roehampton, United Kingdom
Rafia Mumtaz, National University of Sciences and Technology (NUST), Pakistan
Muhammad Khan, National University of Sciences and Technology (NUST), Pakistan

Call for Chapters

Proposals Submission Deadline: October 20, 2024
Full Chapters Due: December 15, 2024
Submission Date: December 15, 2024

Introduction

This book explores how modern technologies like the Internet of Things (IoT) and machine learning can transform the way cities are designed and managed. It aims to provide readers with an understanding of how these technologies can be used to create smarter, more efficient urban environments that are better equipped to handle the challenges of growing populations, climate change, and resource management. By connecting everyday devices to the internet (IoT), cities can collect vast amounts of data, which, when analyzed through machine learning, can lead to more informed decisions about everything from traffic flow to energy usage. This book is a practical guide for city planners, engineers, and anyone interested in how technology can be harnessed to make our urban spaces more sustainable, livable, and responsive to the needs of their residents.

Objective

The objective of the book is to explore and demonstrate how advanced technologies like the Internet of Things (IoT) and machine learning can be applied to urban planning to make cities smarter, more efficient, and more sustainable. The book aims to bridge the gap between theoretical knowledge and practical applications, offering readers a clear understanding of how these technologies can be used to address real-world challenges in urban environments. One of the main goals of the book is to provide a comprehensive guide that explains how IoT can be used to gather valuable data from various sources in a city, such as traffic sensors, environmental monitors, and public services. This data can then be analyzed using machine learning algorithms to identify patterns, predict outcomes, and optimize city management processes. For example, machine learning can help predict traffic congestion and suggest alternative routes or manage energy consumption in buildings more effectively. The book intends to add to and further current research by offering new insights into the integration of IoT and machine learning in urban planning. While there is already significant research on smart cities, this book focuses on the practical implementation of these technologies, providing case studies, examples, and frameworks that can be applied by city planners, engineers, and policymakers. By doing so, it aims to push the boundaries of existing knowledge and encourage more widespread adoption of these technologies in urban planning, ultimately contributing to the development of smarter, more responsive cities.

Target Audience

This book is primarily geared towards professionals and students involved in urban planning, engineering, IT, computer science and city management. This includes urban planners, city officials, civil engineers, architects, and policymakers who are looking to incorporate advanced technologies into their planning and management processes. These professionals will benefit from the book's practical insights into how IoT and machine learning can be used to make cities more efficient, sustainable, and livable. Additionally, the book is also valuable for researchers and academics in the fields of smart cities, urban studies, and technology. It offers a comprehensive exploration of the latest trends and applications of IoT and machine learning in urban environments, making it a useful resource for those conducting research in these areas. Students studying urban planning, engineering, computer science, or related fields will find the book particularly helpful as it provides both theoretical knowledge and practical case studies that can enhance their understanding of how technology can be applied to solve real-world urban challenges. Lastly, technology developers and innovators who are creating IoT devices or machine learning algorithms for urban applications will find this book beneficial. It will give them insights into the needs and challenges of urban planning, helping them design solutions that are better aligned with the demands of modern cities. Overall, anyone interested in the future of urban development and the role of technology in shaping smarter cities will find this book to be an invaluable resource.

Recommended Topics

Introduction to smart urban planning Basics of Internet of Things (IoT) in urban planning Introduction to machine learning in urban planning Integrating IoT and machine learning for smart cities Smart transportation systems Smart energy management Environmental monitoring and sustainability Public safety and security Smart infrastructure and building management Citizen engagement and smart governance Challenges and ethical considerations Future trends in smart urban planning

Submission Procedure

Researchers and practitioners are invited to submit on or before October 20, 2024, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by October 25, 2024 about the status of their proposals and sent chapter guidelines.Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by December 15, 2024, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Leveraging IoT and Machine Learning for Smart Urban Planning. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.



Publisher

This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), an international academic publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2025.



Important Dates

October 20, 2024: Proposal Submission Deadline
October 25, 2024: Notification of Acceptance
December 15, 2024: Full Chapter Submission
January 26, 2025: Review Results Returned
February 23, 2025: Final Acceptance Notification
March 2, 2025: Final Chapter Submission



Inquiries

Muneer Ahmad
University of Roehampton
muneer.ahmad@roehampton.ac.uk

Rafia Mumtaz
National University of Sciences and Technology (NUST)
rafia.mumtaz@seecs.edu.pk

Muhammad Ajmal Khan
National University of Sciences and Technology (NUST)
ajmal.khan@seecs.edu.pk



Classifications


Business and Management; Computer Science and Information Technology; Government and Law; Social Sciences and Humanities; Physical Sciences and Engineering
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