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Learn How to Design and Implement HAR Systems
The pervasiveness and range of capabilities of today’s mobile devices have enabled a wide spectrum of mobile applications that are transforming our daily lives, from smartphones equipped with GPS to integrated mobile sensors that acquire physiological data. Human Activity Recognition: Using Wearable Sensors and Smartphones focuses on the automatic identification of human activities from pervasive wearable sensors―a crucial component for health monitoring and also applicable to other areas, such as entertainment and tactical operations.
Developed from the authors’ nearly four years of rigorous research in the field, the book covers the theory, fundamentals, and applications of human activity recognition (HAR). The authors examine how machine learning and pattern recognition tools help determine a user’s activity during a certain period of time. They propose two systems for performing HAR: Centinela, an offline server-oriented HAR system, and Vigilante, a completely mobile real-time activity recognition system. The book also provides a practical guide to the development of activity recognition applications in the Android framework.
- Sales Rank: #3213783 in Books
- Published on: 2013-12-05
- Original language: English
- Number of items: 1
- Dimensions: 9.20" h x 1.00" w x 6.30" l, 1.45 pounds
- Binding: Hardcover
- 207 pages
From the Author
Please find a demo of Vigilante, our Android HAR application, here:
About the Author
Miguel A. Labrador is an associate professor in the Department of Computer Science and Engineering, the director of the Graduate Programs, and the director of the Research Experiences for Undergraduates Program at the University of South Florida. A senior member of the IEEE and member of ACM, ASEE, and Beta Phi Mu, Dr. Labrador is an area editor of Computer Communications and editorial board member of the Journal of Network and Computer Applications and has published more than 100 technical and educational papers. His research interests include ubiquitous sensing, location-based services, energy-efficient mechanisms for wireless sensor networks, and design and performance evaluation of computer networks and communication protocols. He received a Ph.D. in information science with a concentration in telecommunications from the University of Pittsburgh.
Oscar D. Lara Yejas is part of the IBM InfoSphere BigInsights team. His current work focuses on large-scale analytics in distributed computing environments. He holds a B.Sc. in Systems Engineering from Universidad del Norte, Colombia (2007), as well as a M.Sc. in Computer Science in 2010 and a Ph.D. in Computer Science and Engineering in 2012, both from the University of South Florida. Dr. Lara Yejas also has experience in mobile visualization of geographic and cartographic information, real-time tracking applications, and telemetry. Dr. Lara Yejas' dissertation on human activity recognition with wearable sensors -under the advising of Dr. Labrador- has given birth to this book. Further research interests of his encompass but are not limited to machine learning, big data analytics, location-based systems,as well as multiobjective optimization using swarm intelligence methods.
Most helpful customer reviews
2 of 2 people found the following review helpful.
Human Activity Recognition
By Raj
Received my copy of this book today from amazon. It took just a week for delivery, nicely packed and damage free. For researchers who are working on HAR using smartphone sensors, this is a very good reference and also a good comparison of work.
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