Machine Learning in Java - Second Edition

Introducing activity recognition

Activity recognition is an underpinning step in behavior analysis, addressing healthy lifestyles, fitness tracking, remote assistance, security applications, elderly care, and so on. Activity recognition transforms low-level sensor data from sensors, such as an accelerometer, gyroscope, pressure sensor, and GPS location, to a higher-level description of behavior primitives.

In most cases, these are basic activities, for example, walking, sitting, lying, jumping, and so on, as shown in the following diagram, or they could be more complex behaviors, such as going to work, preparing breakfast, and shopping: