Autonomous and Connected Heavy Vehicle Technology

Autonomous and Connected Heavy Vehicle Technology

1st Edition - February 1, 2022
  • Editor: Fatos Xhafa
  • Paperback ISBN: 9780323905923

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Description

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.

Key Features

  • Covers state-of-the-art developments and research in vehicle sensor technology, vehicle communication technology, convergence with emerging technologies, and vehicle software and hardware integration
  • Addresses challenges such as optimization, real-time control systems for distance and steering mechanism, and cognitive and predictive analysis
  • Provides complete product development, commercial deployment, technological and performing costs and scaling needs

Readership

Those mainly involved in Automotive Engineering and Computer Science: Academicians, Researchers, Postdoc fellows, Research scholars, Graduate and Post-graduate students, Industry-fellows, and Software Engineers

Table of Contents

  • 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

Product details

  • No. of pages: 454
  • Language: English
  • Copyright: © Academic Press 2022
  • Published: February 1, 2022
  • Imprint: Academic Press
  • Paperback ISBN: 9780323905923

About the Series Editor

Fatos Xhafa

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

Affiliations and Expertise

Full Professor of Computer Science, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain

About the Editors

Rajalakshmi Krishnamurthi

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.

Affiliations and Expertise

Assistant Professor (Senior Grade), Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, India

Adarsh Kumar

Adarsh Kumar received his Master degree (M. Tech) in Software Engineering from Thapar University, Patiala, Punjab, India, in 2005 and earned his PhD degree from Jaypee Institute of Information Technology University, Noida, India in 2016 followed by Post-Doc from Software Research Institute, Athlone Institute of Technology, Ireland during 2016-2018. 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. Currently, he is working with University of Petroleum & Energy Studies, Dehradun, India as Associate Professor in School of Computer Science. His main research interests are cybersecurity, cryptography, network security, and ad-hoc networks. He has published 60+ research papers in reputed journals, conferences and workshops. He participated in one multi-billion European Union H2020 sponsored research project and he is currently executing two research projects sponsored from UPES SEED division.

Affiliations and Expertise

Associate Professor, Department of Systemics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India

Sukhpal Gill

Sukhpal Singh Gill is a Lecturer (Assistant Professor) in Cloud Computing at School of Electronic Engineering and Computer Science, Queen Mary University of London, UK. Prior to this, 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 in ETT Wiley and IET Networks Journal. His research interests include Cloud Computing, Fog Computing, Software Engineering, Internet of Things and Healthcare.

Affiliations and Expertise

Assistant Professor, School of Electronic Engineering and Computer Science, Queen Mary University of London, UK.