Data Fusion in Wireless Sensor Networks
A statistical signal processing perspective
The role of data fusion has been expanding in recent years through the incorporation of pervasive applications, where the physical infrastructure is coupled with information and communication technologies, such as wireless sensor networks for the internet of things (IoT), e-health and Industry 4.0. In this edited reference, the authors provide advanced tools for the design, analysis and implementation of inference algorithms in wireless sensor networks.
The book is directed at the sensing, signal processing, and ICTs research communities. The contents will be of particular use to researchers (from academia and industry) and practitioners working in wireless sensor networks, IoT, E-health and Industry 4.0 applications who wish to understand the basics of inference problems. It will also be of interest to professionals, and graduate and PhD students who wish to understand the fundamental concepts of inference algorithms based on intelligent and energy-efficient protocols.
About the Editors
Domenico Ciuonzo was a Researcher at NM-2 s.r.l., Naples, during 2017-18. He is now an Assistant Professor at University of Naples Federico II.
Pierluigi Salvo Rossi is Principal Engineer with the Department of Advanced Analytics and Machine Learning, Kongsberg Digital AS, Norway. He is an IEEE Senior Member, Associate Editor of IEEE Transactions on Wireless Communications, and Senior Editor of IEEE Communications Letters.
Publication Year:
2019
Pages:
352
ISBN-13: 978-1-78561-584-9
Format:
HBK
Editors:
Domenico Ciuonzo, Pierluigi Salvo Rossi