Academic Press Autonomous and Connected Heavy Vehicle Technology (Intelligent Data-Centric Systems)

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. To learn more about Elsevier’s Series, Intelligent Data-Centric Systems, please visit this link: https://www.elsevier.com/books-and-journals/book-series/intelligent-data-centric-systems-sensor-collected-intelligence Review Features next generation technologies for the management of heavy vehicles From the Back Cover <i>Autonomous and Connected Heavy Vehicle Technology </i>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. <p>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.</p> 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. 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, h