[agents] Call for Book Chapters - Empowering IoT with Big Data Analytics

[Zakaria Maamar]

Call for Book Chapters
Empowering IoT with Big Data Analytics: Challenges, Opportunities, and
Prospects

Introduction
Big Data is a multidisciplinary field that involves efficiently managing
continuous, intensive, and heterogeneous data from different sources, such
as sensors, social media, and embedded systems. The emergence of Internet
of Things (IoT) and its application to a wide range of domains, such as
healthcare, logistics, and defence, has led to the generation of huge
amounts of both structured and unstructured data, commonly referred to as
Big Data. From a broad perspective, data must be retrieved, collected,
transmitted, stored, pre-processed, processed, protected, shared, and
analysed in order to gain meaningful insights and support sound decisions.
Throughout these stages, many obstacles could undermine their completion
requiring immediate tackling by communities of researchers, practitioners,
users, etc. These challenges include, but are not limited to,
pre-/post-processing of data, real-time data processing, data privacy and
security, data storage, cost management, data quality, visualization and
personalization of data, integration of various technologies, and
assessment of trade-offs between all these challenges.

The purpose of this book is to provide an in-depth exploration of the major
topics related to empowering the IoT with Big Data technologies and
analytics solutions. This book allows readers to gain a better
understanding of how to process, analyze, protect, distribute, and
visualize data for the benefit of IoT applications and their end-users, as
well as how to effectively deploy IoT applications in the field. It covers
the current state of the art in Big Data and IoT technologies, standards,
platforms, and solutions, and offers a comprehensive view of the Big Data
value-chain for IoT, including storage, processing, protection,
distribution, analytics, and visualization. Additionally, it provides
readers with the tools and techniques needed to analyze Big Data for IoT,
as well as an overview of the challenges associated with handling Big Data
generated from IoT devices.

The book's guest editors are looking for scholars who are interested in
contributing book chapters related to Big Data and IoT for publication by
Elsevier in August 2023. These book chapters should focus on all aspects of
how Big Data analytics can enhance the Internet of Things, and topics
related to this are welcomed, though not limited to::
* Big Data technologies and approaches for processing real-time data
* Big Data analytics approaches and tools of sensory data
* Sensory big data visualization
* Big Data for cognitive IoT applications.
* Big Data for self-healing IoT applications.
* Remote Big Data analytics
* Federated Big Data analytics
* Edge computing for Big Data analytics

Deadlines
* One-page proposal: February 20, 2023
* First Round, Acceptance/Rejection: February 28, 2023
* Full Chapter submission: April 30, 2023
* Chapter reviews (editors and/or double-blind peer review): May 31, 2023
* Editorial decision (Final Acceptance/Revision/Rejection): June 30, 2023
* Chapter revision and final chapter submission: July 31, 2023
* Planned publication: August 31, 2023

Publisher and indexing
Elsevier - Intelligent Data-Centric Systems: Sensor Collected Intelligence,
https://www.elsevier.com/books-and-journals/book-series/intelligent-data-centric-systems-sensor-collected-intelligence

Indexing/Abstracting:
The book is submitted for indexing in:
* Scopus
* EI Indexing / Compendex
* Book Citation Index

Editor information
* M. Adel Serhani, College of Computing and informatics, University of
Sharjah, UAE.
* Yang Xu, School of Computer Science, Fudan University, China.
* Zakaria Maamar, College of Computing and IT, University of Doha for
Science and Technology, Doha, Qatar.

If you have any questions, feel free to contact editors at:
iot.bdbook at gmail.com

Table of contents
* Chapter 1 Foundations of IoT and Big Data (to be co-authored by the
book's editors)
o What is IoT and Big Data?
o How are IoT and Big Data connected?
o What are the main challenges of connecting Big Data and IoT?
* Chapter 2 IoT technologies and architectures
o Emerging IoT-Big Data technologies, and solutions
o Sensing and actuating technologies in IoT
o Software architectures for IoT
o Human Computer interaction in IoT and Big Data UI/UX
* Chapter 3 Big Data architectures for IoT
o Big Data processing platforms for IoT
o Big Data storage systems for IoT
o Big Data visualization for IoT
* Chapter 4 Big Data analytics for IoT
o Why is Big Data analytics important in IoT?
o Technologies Enabling Big Data analytics for IoT
o Algorithms for Big Data delivery over Internet of Things.
* Chapter 5 Machine learning models for sensory data analytics
o Deep learning models for sensory data analytics
o Deep reinforcement learning for IoT Data
o Distributed Machine Learning for Big Data
* Chapter 6 Real time big data Analytics
o Realtime Big data Analytics for IoT
o Streamed sensory data analytics
* Chapter 7 Applications of Big data analytics in IoT
o Sustainable solution for smart cities based IoT and Big Data
o Smart connected health based IoT
o Smart transportation based IoT
* Chapter 8 Security and privacy of IoT applications
o Limitations of existing technologies and approaches
o Big Data to achieve IoT applications security
o Big Data to achieve IoT applications privacy
* Chapter 9 Big Data Quality Assessment in the IoT era
o Quality evaluation and profiling
o Streamed data quality assessment
* Chapter 10 Cognitive IoT applications
o Big Data for cognitive IoT applications
o Big Data for self-healing IoT applications
* Chapter 11 Cloud/edge provisioning to support Big Data and IoT
o Cloud/edge resources provision to support IoT applications
o Cloud/edge platforms to support Big IoT data storage and processing
o Cloud/edge services to support IoT applications
* Chapter 12 Challenges of Big Data an IoT
o Challenges for Big Data and IoT Security
o Security in IoT, Big Data Applications and Services.
* Chapter 13 New trends in Big Data and IoT applications and solutions
o Intelligent sensing and data curation
o Smart IoT and Big Data solutions
o Virtual reality in IoT
* Chapter 14 Case studies of Big Data applications for IoT
o Healthcare case-study
o Finance case-study
o Law enforcement case-study
o Smart Grid and Supply chain Management
* Chapter 15 Networks and Implementation tools for IoT and Big Data.
o Type of IoT Networksĸ
o IoT Protocols (e.g., RPL, 6LoWPAN, ICMPv6, CoAP)
o Operating Systems and Simulators for IoT and Big Data
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