Abstract
Context-aware computing is proposed as an enabling
technology for adaptating different functions in
computer-aided devices. The development of
context-awareness for mobile devices requires recognition
and extraction of implicit context information from the
usage situations and environment of a device. Context
information is provided for applications and services,
which adapt their appearance and functions accordingly.
Mobile devices contain several potential context data
sources such as, location, time and applications. In this
thesis, sensors integrated into a mobile device are
utilised as sources for context information.
The main challenge in sensor-based context-aware
computing for mobile devices is how to define and carry
out context recognition from sensor signals to facilitate
use of context information in mobile applications. In
this thesis we have divided this into specific research
problems: How should low-level context information be
extracted from sensor signals to obtain a rich and usable
representation? How should low-level context information
be processed and examined to obtain higher-level
contexts? How to utilise context representation in
applications? An empiric and data centric approach
including signal processing, feature extraction and
explorative data analysis methods is used in examining
and defining a procedure for sensor-based context
recognition.
The main result of this work is a procedure for
sensor-based context recognition that is demonstrated
with experiments and with the applications developed. The
main technical solutions developed include methods for
extracting context information and converting it into a
suitable context representation, solution for
collaborative recognition of the context of a group of
mobile devices, an approach for controlling mobile
applications and a solution for enhancing remote
communication with context information. The thesis
includes a review of context data processing and the
utilisation of context information in mobile devices.
Original language | English |
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Qualification | Doctor Degree |
Awarding Institution |
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Supervisors/Advisors |
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Award date | 18 Dec 2003 |
Place of Publication | Espoo |
Publisher | |
Print ISBNs | 951-38-6253-4 |
Electronic ISBNs | 951-38-6254-2 |
Publication status | Published - 2003 |
MoE publication type | G5 Doctoral dissertation (article) |
Keywords
- Ubiquitous computing
- pervasive computing
- mobile computing
- pattern recognition
- data exploration
- human-computer interaction