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A comprehensive introduction to the basic principles, design techniques and analytical tools of wireless communications.

The book presents a broad overview of emerging smart grid technologies and communication systems, offering a helpful guide for future research in the field of electrical engineering and communication engineering. It explores recent advances in several computing technologies and their performance evaluation, and addresses a wide range of topics, such as the essentials of smart grids for fifth generation (5G) communication systems. It also elaborates the role of emerging communication systems such as 5G, internet of things (IoT), IEEE 802.15.4 and cognitive radio networks in smart grids. The book includes detailed surveys and case studies on current trends in smart grid systems and communications for smart metering and monitoring, smart grid energy storage systems, modulations and waveforms for 5G networks. As such, it will be of interest to practitioners and researchers in the field of smart grid and communication infrastructures alike.

In the 90s, new languages and architectures were developed, new systems and networks were produced and new applications invented. The basic topics discussed are; High Speed Data Communications Protocols, Services and Networks for high speed data and for combined voice and data applications - i.e. ATM, SMDS, Frame Relay - Network Management, OSS Platforms, OSI and other information Technology Services, Network Control and Routing, Emergency Control and Telecommunication Politics. This publication offers the material basis for propagating the most advanced ideas, products, decisions and results of the 90s, and thereby it celebrates the advancements of Computer Communication on the route towards a new era.

First Published in 2006. Routledge is an imprint of Taylor & Francis, an informa company.

This book covers challenges and solutions in establishing Industry 4.0 standards for Internet of Things. It proposes a clear view about the role of Internet of Things in establishing standards. The sensor design for industrial problem, challenges faced, and solutions are all addressed. The concept of digital twin and complexity in data analytics for predictive maintenance and fault prediction is also covered. The book is aimed at existing problems faced by the industry at present, with the goal of cost-efficiency and unmanned automation. It also concentrates on predictive maintenance and predictive failures. In addition, it includes design challenges and a survey of literature.

'This textbook is clearly a valuable resource for engineering students or anyone who wants to learn about wireless communication since it provides the technical fundamentals of the key theories and methods used for IoT communication … If you are interested in learning about the technical details of IoT and wireless communication, then this very well-written book, loaded with the fundamentals for understanding this rapidly growing system of the future, is well-worth reading.'IEEE Electrical Insulation MagazineThis textbook metamorphosed from notes that the author has been using to teach at four universities in Australia and New Zealand. The book treats the physical principles and design of wireless Internet of Things (IoT) systems from engineering perspective. IoT enables communication between people, between people and things, and between things. The book highlights the wide scope of sensors used in IoT - including RFIDs, smart mobile phones, home consumer devices, autonomous cars, utility meters, car park meters, robots, satellites, radars and wireless positioning systems. Three features render the book practically accessible. First, each chapter is organised in sections, each of which ends with a set of authentic review questions to motivate reflection. This is complemented by numerous worked examples in each section. Third, the book introduces two popular industry software packages for hands-on practice — MATLAB® and CelPlanner™. With the growing popularity of softwarisation and cloudification, possessing expertise in these packages makes one useful to the industry. Parts of this book are taught in undergraduate curriculum, while the rest is taught in graduate courses. Both traditional and modern topics including C-RAN, network slicing, NFV, NB-IoT and 5G use cases in IoT are covered.Instructor's resources are provided for free to instructors who adopt the book as textbook for a unit/ course/subject/paper. Please send your request to sales@wspc.com.

"Organised by Wessex Institute of Technology, UK; University of Antwerp, Belgium; University of Rome 'La Sapienza', Italy" - prelim.

Engineers have attempted to solve water resources engineering problems with the help of empirical, regression-based and numerical models. Empirical models are not universal, nor are regression-based models. The numerical models are, on the other hand, physics-based but require substantial data measurement and parameter estimation. Hence, there is a need to employ models that are robust, user-friendly, and practical and that do not have the shortcomings of the existing methods. Artificial intelligence methods meet this need. Soft Computing in Water Resources Engineering introduces the basics of artificial neural networks (ANN), fuzzy logic (FL) and genetic algorithms (GA). It gives details on the feed forward back propagation algorithm and also introduces neuro-fuzzy modelling to readers. Artificial intelligence method applications covered in the book include predicting and forecasting floods, predicting suspended sediment, predicting event-based flow hydrographs and sedimentographs, locating seepage path in an earth-fill dam body, and the predicting dispersion coefficient in natural channels. The author also provides an analysis comparing the artificial intelligence models and contemporary non-artificial intelligence methods (empirical, numerical, regression, etc.). The ANN, FL, and GA are fairly new methods in water resources engineering. The first publications appeared in the early 1990s and quite a few studies followed in the early 2000s. Although these methods are currently widely known in journal publications, they are still very new for many scientific readers and they are totally new for students, especially undergraduates. Numerical methods were first taught at the graduate level but are now taught at the undergraduate level. There are already a few graduate courses developed on AI methods in engineering and included in the graduate curriculum of some universities. It is expected that these courses, too, will soon be taught at the undergraduate levels.