Activity Learning: Discovering, Recognizing, and Predicting by Diane J. Cook PDF

By Diane J. Cook

ISBN-10: 111889376X

ISBN-13: 9781118893760

Defines the concept of an task version realized from sensor info and offers key algorithms that shape the middle of the field

Activity studying: studying, spotting and Predicting Human habit from Sensor Data presents an in-depth examine computational ways to task studying from sensor info. every one bankruptcy is built to supply useful, step by step details on find out how to study and strategy sensor facts. The publication discusses ideas for task studying that come with the following:

  • Discovering task styles that emerge from behavior-based sensor data
  • Recognizing occurrences of predefined or chanced on actions in actual time
  • Predicting the occurrences of activities

The ideas lined should be utilized to varied fields, together with protection, telecommunications, healthcare, clever grids, and residential automation. an internet spouse web site allows readers to scan with the innovations defined within the publication, and to evolve or increase the recommendations for his or her personal use.

With an emphasis on computational methods, Activity studying: studying, spotting, and Predicting Human habit from Sensor Data offers graduate scholars and researchers with an algorithmic viewpoint to task learning.

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

Example text

Each wearable sensor reports six values: acceleration in the x, y, z directions and rotational velocity around the x, y, and z axes. In the Hand Washing activity, the participant washes her hands at the kitchen sink using hand soap that is located in a dispenser next to the sink. After her hands are washed, she uses a cloth towel also located in the kitchen to dry her hands. 10 the timing of sensor events corresponding to the sensor data are plotted. 12 for one participant and the corresponding sensor data are provided in Appendix 1.

1 Sensors in the Environment Some sensors that monitor activities are not affixed to the individuals performing the activity but are placed in the environment surrounding the individual. These sensors are valuable in passively providing readings without requiring individuals to comply with rules regarding wearing or carrying sensors in prescribed manners. Because they are not customized for each person, environment sensors can monitor activities for a group of individuals but may have difficulty separating movements or actions among individuals that are part of that group.

16) i=1 • Peak-to-Peak Amplitude. This value represents the change between the peak (highest value) and trough (lowest value) of the signal. For sensor values, we can compute the difference between the maximum and minimum values of the set. 17) • Time Between Peaks. This value represents the time delay between successive occurrences of a maximum value. When processing sensor values that are not strictly sinusoidal signals, special attention must be paid to determine what constitutes a peak. A peak may be a value within a fixed range of the maximum value, or it may be a spike or sudden increase in values.

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Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data by Diane J. Cook

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