Activity recognition is an underpinning step in behavior analysis, addressing healthy lifestyle, fitness tracking, remote assistance, security applications, elderly care, and so on. Activity recognition transforms low-level sensor data from sensors, such as 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 image, or they could be more complex behaviors, such as going to work, preparing breakfast, shopping, and so on:
In this chapter, we will discuss how to add the activity recognition functionality into a mobile application. We will first look at what does an activity recognition problem looks like, what kind of data do we need to collect, what are the main challenges are, and how to address them?
Later, we will follow an example to see how to actually implement activity...