Activity Learning: Discovering, Recognizing, And Predicting Human Behavior From Sensor Data

This book provides a comprehensive description of activity learning with techniques, details on existing algorithms, and case studies of technique applications to sensor datasets. Each chapter is constructed to provide practical, step by step information on how to analyze and process sensor data.

• Discusses potential real-world complications and provides step-by-step methods to manage or offset them
• Includes case studies, coded examples, and data sets for the reader's use
• An online companion site enables readers to experiment with the techniques described in the book, and to adapt or enhance the techniques for their own use

Diane Cook, PhD, is a professor in the School of Electrical Engineering and Computer Science at Washington State University. Her research relating to artificial intelligence and data mining have been supported by grants from the National Science Foundation, the National Institutes of Health, NASA, DARPA, USAF, NRL, and DHS. She is the co-author of Mining Graph Data and Smart Environments, both published by Wiley. Dr. Cook is an IEEE Fellow and a member of AAAI.

Narayanan C. Krishnan, PhD, is a faculty member of the Department of Computer Science and Engineering at the Indian Institute of Technology Ropar. His research focuses on activity recognition, pervasive computing, and applied machine learning. Dr. Krishnan received the gold medal for academic excellence in Masters of Technology in Computer Science in 2004 and was nominated for the Best PhD Thesis Award at Arizona State University in 2010.