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Data Fusion in Wireless Sensor Networks: A statistical signal processing perspective

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  • Дата: 5-08-2019, 20:17
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Название: Data Fusion in Wireless Sensor Networks: A statistical signal processing perspective
Автор: Domenico Ciuonzo, Pierluigi Salvo Rossi
Издательство: The Institution of Engineering and Technology
Год: 2019
Страниц: 349
Язык: английский
Формат: pdf (true)
Размер: 21.5 MB

The Internet-of-Things revolution is coming to reality and most of real-life scenarios are experiencing the pervasive presence of network-enabled devices, in most cases sensors. The deployment of heterogeneous sensors at several locations enables collection of different kinds of (big amount of) data about the surrounding scenario. A wireless sensor network is the typical solution for data collection, data processing, and inference in most of Internet-of-Things applications.

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.

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