Internet of Things and Big Data Analytics for Smart Generation
Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing
| Author: | ISBN: | 9783030042035 | |
| Publisher: | Springer International Publishing | Publication: | December 30, 2018 |
| Imprint: | Springer | Language: | English |
| Author: | |
| ISBN: | 9783030042035 |
| Publisher: | Springer International Publishing |
| Publication: | December 30, 2018 |
| Imprint: | Springer |
| Language: | English |
This book discusses emerging technologies in the field of the Internet of Things and big data, an area that will be scaled in next two decades.
Written by a team of leading experts, it is the only book focusing on the broad areas of both the Internet of things and big data. The thirteen chapters present real-time experimental methods and theoretical explanations, as well as the implementation of these technologies through various applications.
Offering a blend of theory and hands-on practices, the book enables graduate, postgraduate and research students who are involved in real-time project scaling techniques to understand projects and their execution. It is also useful for senior computer students, researchers and industry workers who are involved in experimenting with the Internet of Things and big data technologies, helping them to solve the real-time problem. Moreover, the chapters covering cutting-edge technologies help multidisciplinary researchers who are bridging the gap of two different outset real-time problems.
This book discusses emerging technologies in the field of the Internet of Things and big data, an area that will be scaled in next two decades.
Written by a team of leading experts, it is the only book focusing on the broad areas of both the Internet of things and big data. The thirteen chapters present real-time experimental methods and theoretical explanations, as well as the implementation of these technologies through various applications.
Offering a blend of theory and hands-on practices, the book enables graduate, postgraduate and research students who are involved in real-time project scaling techniques to understand projects and their execution. It is also useful for senior computer students, researchers and industry workers who are involved in experimenting with the Internet of Things and big data technologies, helping them to solve the real-time problem. Moreover, the chapters covering cutting-edge technologies help multidisciplinary researchers who are bridging the gap of two different outset real-time problems.
