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Published Articles >> Table of Contents >> Abstract
Fifth IEEE Workshop on Mobile Computing Systems & Applications
p. 129
Proximity Mining: Finding Proximity using Sensor Data History
Toshihiro Takada, NTT Corporation
Satoshi Kurihara, NTT Corporation
Toshio Hirotsu, NTT Corporation
Toshiharu Sugawara, NTT Corporation
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCSA.2003.1240774
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| Abstract |
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Emerging ubiquitous and pervasive computing
applications often need to know where things are
physically located. To meet this need, many location-sensing
systems have been developed, but none of the
systems for the indoor environment have been widely
adopted. In this paper we propose Proximity Mining, a
new approach to build location information by mining
sensor data. The Proximity Mining does not use geometric
views for location modeling, but automatically discovers
symbolic views by mining time series data from sensors
which are placed in surroundings. We deal with trend
curves representing time series sensor data, and use their
topological characteristics to classify locations where the
sensors are placed.
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 Additional Information
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Index Terms- Proxymity Mining; Location modeling; Zero
configuration; Location-aware computing; Context-aware
computing; Pervasive computing; Ubiquitous computing;
Spatial Data Mining; Real-space computing
Citation:
Toshihiro Takada, Satoshi Kurihara, Toshio Hirotsu, Toshiharu Sugawara,
"Proximity Mining: Finding Proximity using Sensor Data History,"
wmcsa,
p. 129,
Fifth IEEE Workshop on Mobile Computing Systems & Applications,
2003
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