$206.49
Author: Krishnamurthi Rajalakshmi
Edition: 1
Number Of Pages: 454
Details: From the Back Cover
Autonomous and Connected Heavy Vehicle Technology presents the fundamentals, definitions, technologies, standards, and future developments of autonomous and connected heavy vehicles. This book provides insight into various issues pertaining to heavy vehicle technology and helps to 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 are covered related to connected vehicles along with concepts such as edge computing, dynamic resource optimization, engineering process and methodology, and future directions. It also contains a wide range of case studies that help to identify research problems, an analysis of the issues and synthesis solutions.
An essential resource for graduate-level students from different engineering disciplines such as automotive and mechanical engineering, computer science, data science and business analytics, this book combines both basic concepts and advanced level contents from technical experts towards the advancement of emerging technologies in applications of heavy vehicle technology.
Product 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.
Review
Features next generation technologies for the management of heavy vehicles
About the Author
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.
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.
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, U
Release Date: 24-01-2022
Package Dimensions: 27x235x840
