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DOI: 10.14569/IJACSA.2015.060216
PDF

GPS-Based Daily Context Recognition for Lifelog Generation Using Smartphone

Author 1: Go Tanaka
Author 2: Masaya Okada
Author 3: Hiroshi Mineno

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 6 Issue 2, 2015.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Mobile devices are becoming increasingly more sophisticated with their many diverse and powerful sensors, such as GPS, acceleration, and gyroscope sensors. They provide numerous services for supporting daily human life and are now being studied as a tool to reduce the worldwide increase of lifestyle-related diseases. This paper describes a method for recognizing the contexts of daily human life by recording a lifelog based on a person’s location. The proposed method can distinguish and recognize several contexts at the same location by extracting features from the GPS data transmitted from smartphones. The GPS data are then used to generate classification models by machine learning. Five classification models were generated: a mobile or stationary recognition model, a transportation recognition model, and three daily context recognition models. In addition, optimal learning algorithms for machine learning were determined. The experimental results show that this method is highly accurate. As examples, the F-measure of the daily context recognition was approximately 0.954 overall at a tavern and approximately 0.920 overall at a university .

Keywords: component; Lifelog, machine learning, GPS, healthcare

Go Tanaka, Masaya Okada and Hiroshi Mineno, “GPS-Based Daily Context Recognition for Lifelog Generation Using Smartphone” International Journal of Advanced Computer Science and Applications(IJACSA), 6(2), 2015. http://dx.doi.org/10.14569/IJACSA.2015.060216

@article{Tanaka2015,
title = {GPS-Based Daily Context Recognition for Lifelog Generation Using Smartphone},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.060216},
url = {http://dx.doi.org/10.14569/IJACSA.2015.060216},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {2},
author = {Go Tanaka and Masaya Okada and Hiroshi Mineno}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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