Data Fusion in Wireless Sensor Networks
Institution of Engineering and Technology (Verlag)
978-1-78561-584-9 (ISBN)
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.
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.
Part I: Sensing model uncertainty
Chapter 1: Generalized score-tests for decision fusion with sensing model uncertainty
Chapter 2: Compressed distributed detection and estimation
Chapter 3: Heterogeneous sensor data fusion by deep learning
Part II: Reporting channel uncertainty
Chapter 4: Energy-efficient clustering and collision-aware distributed detection/estimation in random-access-based WSNs
Chapter 5: Channel-aware decision fusion in MIMO wireless sensor networks
Chapter 6: Channel-aware detection and estimation in the massive MIMO regime
Part III: Distributed inference over graphs
Chapter 7: Decentralized detection via running consensus
Chapter 8: Distributed recursive testing of composite hypothesis in multi-agent networks
Chapter 9: Expectation-maximisation based distributed estimation in sensor networks
Part IV: Cross-layer issues
Chapter 10: Distributed estimation in energy harvesting wireless sensor networks
Chapter 11: Secure estimation in wireless sensor networks in the presence of an eavesdropper
Chapter 12: Robust fusion of unreliable data sources using error-correcting output codes
Chapter 13: Conclusions and future perspectives
| Erscheinungsdatum | 07.05.2019 |
|---|---|
| Reihe/Serie | Control, Robotics and Sensors |
| Verlagsort | Stevenage |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Themenwelt | Mathematik / Informatik ► Informatik |
| Technik ► Nachrichtentechnik | |
| ISBN-10 | 1-78561-584-X / 178561584X |
| ISBN-13 | 978-1-78561-584-9 / 9781785615849 |
| Zustand | Neuware |
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