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Semantics in Mobile Sensing (Paperback)
Loot Price: R1,053
Discovery Miles 10 530
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Semantics in Mobile Sensing (Paperback)
Series: Synthesis Lectures on Data, Semantics, and Knowledge
Expected to ship within 10 - 15 working days
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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sensors are being rapidly superseded by various embedded sensors in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.
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