Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data

The book provides a comprehensive overview of techniques for activity learning. These techniques include the ability to discover activities patterns that emerge from behavior-based sensor data; to recognize occurrences of predefined or discovered activities in real time from sensor data; and to pred [...]
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The book provides a comprehensive overview of techniques for activity learning. These techniques include the ability to discover activities patterns that emerge from behavior-based sensor data; to recognize occurrences of predefined or discovered activities in real time from sensor data; and to predict the occurrence of activities. This book provides a comprehensive, foundational description of activity learning, with techniques, details on existing algorithms, and case studies of technique applications to actual sensor datasets.Each chapter provides practical, step-by-step information on how to analyze and process sensor data for activity learning. In addition, the techniques are applicable to numerous sensor platforms. For example, they may be applied to data collected from sensors embedded in a smart environment; from smart phones or wearable sensors; from object sensors; or from cameras. Datasets and tools are provided on an online companion site that allows readers to experiment with the techniques described, and to adapt or enhance them for their own use.