Context awareness is major component of Ambient Intelligence. In fact, Ambient Intelligent environments are designed to combine ubiquity, awareness, intelligence and natural interaction. Awareness is defined as the ability by the system to locate and recognize people and objects, and their intentions. Then, intelligence is the ability of the system to analyze the detected context and to adapt its behavior to people and situations, and to learn over time, in order to provide users with personalized services. These concepts date back to late'90, but nowadays the widespread and ubiquitous availability of mobile devices, equipped with several different sensors, allows to put them into practice in a number of unexpected ways. This work presents a preliminary investigation on the possibility to use some of the smartphone sensors, namely the accelerometer and the gyroscope, to identify the bodily context when the user lifts the device to answer a call. The arm gesture, i.e., the way it is performed, is classified into 4 different states: While standing, sitting, walking or running. This information can be used to trigger context-sensitive system actions.

What are you doing while answering your smartphone?

Abate, Andrea F.;Barra, Silvio;
2018-01-01

Abstract

Context awareness is major component of Ambient Intelligence. In fact, Ambient Intelligent environments are designed to combine ubiquity, awareness, intelligence and natural interaction. Awareness is defined as the ability by the system to locate and recognize people and objects, and their intentions. Then, intelligence is the ability of the system to analyze the detected context and to adapt its behavior to people and situations, and to learn over time, in order to provide users with personalized services. These concepts date back to late'90, but nowadays the widespread and ubiquitous availability of mobile devices, equipped with several different sensors, allows to put them into practice in a number of unexpected ways. This work presents a preliminary investigation on the possibility to use some of the smartphone sensors, namely the accelerometer and the gyroscope, to identify the bodily context when the user lifts the device to answer a call. The arm gesture, i.e., the way it is performed, is classified into 4 different states: While standing, sitting, walking or running. This information can be used to trigger context-sensitive system actions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/265394
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