  Recently, there has been an increase in industrial and academic research on
data-driven analytics with smartphones based on the collection of app usage
patterns and surrounding context data. The Android mobile operating system
utilizes Usage Statistics API (US API) and Accessibility Service API (AS API)
as representative APIs to passively collect app usage data. These APIs are used
for various research purposes as they can collect app usage patterns (e.g., app
status, usage time, app name, user interaction state, and smartphone use state)
and fine-grained data (e.g., user interface elements \& hierarchy and user
interaction type \& target \& time) of each application. In addition, other
sensing APIs help to collect the user's surroundings context (location,
network, ambient environment) and device state data, along with AS/US API. In
this review, we provide insights on the types of mobile usage and sensor data
that can be collected for each research purpose by considering Android built-in
APIs and sensors (AS/US API, and other sensing APIs). Moreover, we classify the
research purposes of the surveyed papers into four categories and 17
sub-categories, and create a hierarchical structure for data classification,
comprising three layers. We present the important trends in the usage of
Android's built-in APIs and sensors, including AS/US API, the types of data
collected using the presented APIs, and discuss the utilization of mobile usage
and sensor data in future research.
