The dramatic progress of smartphone technologies has ushered in a new era of mobile sensing
where traditional wearable on-body sensors are being rapidly superseded by various embedded
sensors in our smartphones. For example a typical smartphone today has at the very least a
GPS WiFi Bluetooth triaxial accelerometer and gyroscope. Alongside new accessories are
emerging such as proximity magnetometer barometer temperature and pressure sensors. Even
the default microphone can act as an acoustic sensor to track noise exposure for example. These
sensors act as a lens to understand the user's context along different dimensions.Data can be
passively collected from these sensors without interrupting the user. As a result this new era
of mobile sensing has fueled significant interest in understanding what can be extracted from
such sensor data both instantaneously as well as considering volumes of time series from these
sensors. For example GPS logs can be used to determine automatically the significant places
associated to a user's life (e.g. home office shopping areas). The logs may also reveal
travel patterns and how a user moves from one place to another (e.g. driving or using public
transport). These may be used to proactively inform the user about delays relevant promotions
from shops in his regular route. Similarly accelerometer logs can be used to measure a user's
average walking speed compute step counts gait identification and estimate calories burnt
per day. The key objective is to provide better services to end users.The objective of this
book is to inform the reader of the methodologies and techniques for extracting meaningful
information (called semantics) from sensors on our smartphones. These techniques form the
cornerstone of several application areas utilizing smartphone sensor data. We discuss technical
challenges and algorithmic solutions for modeling and mining knowledge from smartphone-resident
sensor data streams. This book devotes two chapters to dive deep into a set of highly available
commoditized sensors---the positioning sensor (GPS) and motion sensor (accelerometer).
Furthermore this book has a chapter devoted to energy-efficient computation of semantics as
battery life is a major concern on user experience.
