InContexto: Multisensor Architecture to Obtain People Context from Smartphones
The way users intectact with smartphones is changing after the improvements made in their embedded sensors. Increasingly, these devices are being employed as tools to observe individuals habits. Smartphones provide a great set of embedded sensors, such as accelerometer, digital compass, gyroscope, G...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-04-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2012/758789 |
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| _version_ | 1832547823791374336 |
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| author | Gonzalo Blázquez Gil Antonio Berlanga José M. Molina |
| author_facet | Gonzalo Blázquez Gil Antonio Berlanga José M. Molina |
| author_sort | Gonzalo Blázquez Gil |
| collection | DOAJ |
| description | The way users intectact with smartphones is changing after the improvements made in their embedded sensors. Increasingly, these devices are being employed as tools to observe individuals habits. Smartphones provide a great set of embedded sensors, such as accelerometer, digital compass, gyroscope, GPS, microphone, and camera. This paper aims to describe a distributed architecture, called inContexto, to recognize user context information using mobile phones. Moreover, it aims to infer physical actions performed by users such as walking, running, and still. Sensory data is collected by HTC magic application made in Android OS, and it was tested achieving about 97% of accuracy classifying five different actions (still, walking and running). |
| format | Article |
| id | doaj-art-08342644990743ea805b7f113b098305 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2012-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-08342644990743ea805b7f113b0983052025-02-03T06:43:08ZengWileyInternational Journal of Distributed Sensor Networks1550-14772012-04-01810.1155/2012/758789InContexto: Multisensor Architecture to Obtain People Context from SmartphonesGonzalo Blázquez GilAntonio BerlangaJosé M. MolinaThe way users intectact with smartphones is changing after the improvements made in their embedded sensors. Increasingly, these devices are being employed as tools to observe individuals habits. Smartphones provide a great set of embedded sensors, such as accelerometer, digital compass, gyroscope, GPS, microphone, and camera. This paper aims to describe a distributed architecture, called inContexto, to recognize user context information using mobile phones. Moreover, it aims to infer physical actions performed by users such as walking, running, and still. Sensory data is collected by HTC magic application made in Android OS, and it was tested achieving about 97% of accuracy classifying five different actions (still, walking and running).https://doi.org/10.1155/2012/758789 |
| spellingShingle | Gonzalo Blázquez Gil Antonio Berlanga José M. Molina InContexto: Multisensor Architecture to Obtain People Context from Smartphones International Journal of Distributed Sensor Networks |
| title | InContexto: Multisensor Architecture to Obtain People Context from Smartphones |
| title_full | InContexto: Multisensor Architecture to Obtain People Context from Smartphones |
| title_fullStr | InContexto: Multisensor Architecture to Obtain People Context from Smartphones |
| title_full_unstemmed | InContexto: Multisensor Architecture to Obtain People Context from Smartphones |
| title_short | InContexto: Multisensor Architecture to Obtain People Context from Smartphones |
| title_sort | incontexto multisensor architecture to obtain people context from smartphones |
| url | https://doi.org/10.1155/2012/758789 |
| work_keys_str_mv | AT gonzaloblazquezgil incontextomultisensorarchitecturetoobtainpeoplecontextfromsmartphones AT antonioberlanga incontextomultisensorarchitecturetoobtainpeoplecontextfromsmartphones AT josemmolina incontextomultisensorarchitecturetoobtainpeoplecontextfromsmartphones |