Authors:
- Provides a robust introduction to the main concepts and principles of pervasive computing
- Filled with many real-life examples of typical modern intelligent systems
- Offers many exercises to further deepen readers understanding and knowledge
- Includes practical tutorials to build your own smart systems with little or no previous programming or robotics experience
- Includes supplementary material: sn.pub/extras
Part of the book series: Undergraduate Topics in Computer Science (UTICS)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
About this book
The author explores a range of topics including data acquisition, signal processing, control theory, machine learning and system engineering explaining, with the use of simple mathematical concepts, the core principles underlying pervasive computing systems. Real-life examples are applied throughout, including self-driving cars, automatic insulin pumps, smart homes, and social robotic companions, with each chapter accompanied by a set of exercises for the reader. Practical tutorials are also available to guide enthusiastic readers through the process of building a smart system using cameras, microphones and robotic kits. Due to the power of MATLAB™, this can be achieved with no previous programming or robotics experience.
Although Pervasive Computing is primarily for undergraduate students, the book is accessible to a wider audience of researchers and designers who are interested in exploring pervasive computing further.
Authors and Affiliations
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Department of Computer Science, Vrije Universiteit Amsterdam Department of Computer Science, Amsterdam, The Netherlands
Natalia Silvis-Cividjian
About the author
Bibliographic Information
Book Title: Pervasive Computing
Book Subtitle: Engineering Smart Systems
Authors: Natalia Silvis-Cividjian
Series Title: Undergraduate Topics in Computer Science
DOI: https://doi.org/10.1007/978-3-319-51655-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2017
Softcover ISBN: 978-3-319-51654-7Published: 23 February 2017
eBook ISBN: 978-3-319-51655-4Published: 15 February 2017
Series ISSN: 1863-7310
Series E-ISSN: 2197-1781
Edition Number: 1
Number of Pages: XVIII, 210
Number of Illustrations: 84 b/w illustrations, 99 illustrations in colour
Topics: Artificial Intelligence, Pattern Recognition, Software Engineering, Models and Principles, Computer Engineering