Autonomous and Connected Heavy Vehicle Technology presents the fundamentals, definitions, technologies, standards and future developments of autonomous and connected heavy vehicles. This book provides insights into various issues pertaining to heavy vehicle technology and helps users develop solutions towards autonomous, connected, cognitive solutions through the convergence of Big Data, IoT, cloud computing and cognition analysis. Various physical, cyber-physical and computational key points related to connected vehicles are covered, along with concepts such as edge computing, dynamic resource optimization, engineering process, methodology and future directions.
The book also contains a wide range of case studies that help to identify research problems and an analysis of the issues and synthesis solutions. This essential resource for graduate-level students from different engineering disciplines such as automotive and mechanical engineering, computer science, data science and business analytics combines both basic concepts and advanced level content from technical experts.
Autonomous and Connected Heavy Vehicle Technology presents the fundamentals, definitions, technologies, standards and future developments of autonomous and connected heavy vehicles. This book provides insights into various issues pertaining to heavy vehicle technology and helps users develop solutions towards autonomous, connected, cognitive solutions through the convergence of Big Data, IoT, cloud computing and cognition analysis. Various physical, cyber-physical and computational key points related to connected vehicles are covered, along with concepts such as edge computing, dynamic resource optimization, engineering process, methodology and future directions.
The book also contains a wide range of case studies that help to identify research problems and an analysis of the issues and synthesis solutions. This essential resource for graduate-level students from different engineering disciplines such as automotive and mechanical engineering, computer science, data science and business analytics combines both basic concepts and advanced level content from technical experts.
SECTION 1 Review articles
1 Lightweight and heavyweight technologies for autonomous vehicles:
A survey
2 Cybercrimes and defense approaches in vehicular networks
3 Autonomous driving systems and experiences: A comprehensive
survey
4 Applications of blockchain in automated heavy vehicles:
Yesterday, today, and tomorrow
5 Eco-routing navigation systems in electric vehicles: A
comprehensive survey
SECTION 2 Implementation or Simulation-based study for heavy
vehicles technologies
6 Automatic vehicle number plate detection and recognition systems:
Survey and implementation
7 A secured IoT parking system based on smart sensor communication
with two-step user verification
8 Man-and-wife coupling and need for artificially intelligent heavy
vehicle technology in The Long, Long Trailer
9 Pulse oximeter-based machine learning models for sleep apnea
detection in heavy vehicle drivers
10 Using wavelet transformation for acoustic signal processing in
heavy vehicle detection and classification
11 Congestion control mechanisms in vehicular networks: A
perspective on Internet of vehicles (IoV)
12 Smart traffic light management system for heavy vehicles
13 Smart automated system for classification of emergency heavy
vehicles and traffic light controlling
14 Implementation of a cooperative intelligent transport system
utilizing weather and road observation data
SECTION 3 Applications and case studies for heavy vehicles
technologies
15 Heavy vehicle defense procurement use cases and system design
using blockchain technology
16 Cybercriminal approaches in big data models for automated heavy
vehicles
17 Modeling fuel economy of connected vehicle based on road
dynamics and driving style
18 Conceptual design and computational investigations of fixed wing
unmanned aerial vehicle for medium-range applications
19 Multi-sensor fusion in autonomous heavy vehicles
20 Smart vehicle accident detection for flash floods
Rajalakshmi Krishnamurthi is a Senior Member of IEEE, Professional
Member of ACM, SIAM, IET and CSI. She is serving as Treasurer,
Delhi ACM-W chapter. She is currently working as Assistant
Professor (Senior Grade), Department of Computer Science and
Engineering, Jaypee Institute of Information Technology, Noida,
India. She has more than 17 year of teaching experience. She has
more than 50 research publications in various reputed peer reviewed
International Journal, Book Chapters, and International
Conferences. Her research interest includes Internet of Things,
Cloud Computing, optimization techniques in wireless mobile
networks, e-learning applications using mobile platform and
advanced fuzzy approaches. Dr. Adarsh Kumar is an Professor in the
School of Computer Science with University of Petroleum & Energy
Studies, Dehradun, India. He received his Master degree (M. Tech)
in Software Engineering from Thapar University, Patiala, Punjab,
India and earned his PhD degree from Jaypee Institute of
Information Technology University, Noida, India followed by
Post-Doc from Software Research Institute, Athlone Institute of
Technology, Ireland. From 2005 to 2016, he has been associated with
the Department of Computer Science Engineering & Information
Technology, Jaypee Institute of Information Technology, Noida,
Uttar-Pardesh, India, where he worked as Assistant Professor. His
main research interests are cybersecurity, cryptography, network
security, and ad-hoc networks. He has many research papers in
reputed journals, conferences and workshops. He participated in one
European Union H2020 sponsored research project and he is currently
executing two research projects sponsored from UPES SEED division
and one sponsored from Lancaster University. Dr. Sukhpal Singh Gill
is a Lecturer and Assistant Professor in Cloud Computing at the
School of Electronic Engineering and Computer Science, Queen Mary
University of London, UK. Prior to his present stint, Dr. Gill has
held positions as a Research Associate at the School of Computing
and Communications, Lancaster University, UK and also as a
Postdoctoral Research Fellow at CLOUDS Laboratory, The University
of Melbourne, Australia. Dr. Gill is serving as an Associate Editor
for Wiley ETT and IET Networks Journal. He has co-authored 100+
peer-reviewed papers and has published in prominent international
journals and conferences such as IEEE TCC, IEEE TSC, IEEE TII, IEEE
TNSM, IEEE IoT Journal, Elsevier JSS/FGCS, IEEE/ACM UCC, and IEEE
CCGRID. He has received several awards, including the Distinguished
Reviewer Award from SPE (Wiley), Best Paper Award AusPDC at ACSW
2021, and has also served as the PC member for venues such as
PerCom, UCC, CCGRID, CLOUDS, ICFEC, AusPDC. He has edited research
books for Springer, Elsevier and CRC Press. His research interests
include Cloud Computing, Fog Computing, Software Engineering,
Internet of Things and Energy Efficiency. Fatos Xhafa, PhD in
Computer Science, is Full Professor at the Technical University of
Catalonia (UPC), Barcelona, Spain. He has held various tenured and
visiting professorship positions. He was a Visiting Professor at
the University of Surrey, UK (2019/2020), Visiting Professor at the
Birkbeck College, University of London, UK (2009/2010) and a
Research Associate at Drexel University, Philadelphia, USA
(2004/2005). He was a Distinguished Guest Professor at Hubei
University of Technology, China, for the duration of three years
(2016-2019). Prof. Xhafa has widely published in peer reviewed
international journals, conferences/workshops, book chapters,
edited books and proceedings in the field (H-index 55). He has been
awarded teaching and research merits by the Spanish Ministry of
Science and Education, by IEEE conferences and best paper awards.
Prof. Xhafa has an extensive editorial service. He is founder and
Editor-In-Chief of Internet of Things - Journal - Elsevier (Scopus
and Clarivate WoS Science Citation Index) and of International
Journal of Grid and Utility Computing, (Emerging Sources Citation
Index), and AE/EB Member of several indexed Int'l Journals. Prof.
Xhafa is a member of IEEE Communications Society, IEEE Systems, Man
& Cybernetics Society and Founder Member of Emerging Technical
Subcommittee of Internet of Things.
His research interests include IoT and Cloud-to-thing continuum
computing, massive data processing and collective intelligence,
optimization, security and trustworthy computing and machine
learning, among others. He can be reached at fatos@cs.upc.edu.
Please visit also http://www.cs.upc.edu/~fatos/ and at
http://dblp.uni-trier.de/pers/hd/x/Xhafa:Fatos
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