Publication/Creation Date

September 9 2015

Creators/Contributors

Masayuki Okamoto (creator)
Cheng Chen (creator)
Waseda University (contributor)
Toshiba Corporation (contributor)

Description

This paper presents an improvement for GPS-based indoor-outdoor detection with moving direction information. First, we considered several features based on raw GPS satellite information as the baseline. From the evaluation with GPS data from 19 persons, the SVM-based classifier using a combination of elevation and S/N ratio achieved over 96% accuracy for the simple ‘clear’ situation. Then we introduced direction information from a compass sensor to increase the detection robustness in the canyon of buildings. The second experimentation result showed the proposed method considering direction information kept almost the same accuracy of indoor-outdoor detection in a ‘canyon’ situation, whereas the baseline classifier worsened accuracy by 10%.

Augments

Informing, Interacting, Thinking, Seeing, Hearing, Moving

Technology Keywords

Indoor-Outdoor Detection, Smartphones, Global Positioning System (GPS), Compass Sensor, Support Vector Machine (SVM), Information Interfaces, Satellite ID, Signal/Noise Ratio (SNR)

Keywords

Direction, Experiments, Posters, Research , Study

Marketing Keywords

Corporate R&D Center , Toshiba, Graduate School Of Information Production And Systems , Waseda University

Source

https://www.researchgate.net/publication/281591212_Improving_GPS-based_Indoor-Outdoor_Detection_with_Moving_Direction_Information_from_Smartphone