When evacuating a building after a disaster such as an earthquake, it would be useful to detect the trajectory of an evacuation path by pedestrian dead reckoning (PDR) and record it in a person’s smartphone; this could help rescue staff to trace back to where an injured person remains in the building. Considering this application, we present a novel scheme to recognize motion states of a person, including walking, descending stairs, and ascending stairs, using the person’s smartphone, focusing on the angle of the thigh detected by a rotation vector sensor and acceleration values. The proposed scheme mainly solves the existing problem of height estimation using barometers, in which sensors have a time lag of their output, giving inaccurate estimation. Also, the main benefit of the proposed scheme compared with related works is that it requires only these sensor values obtained when the person is walking or running on one floor of a building as reference values, which are used to recognize other motion states, where the scheme requires training data of only a part of the target motion states for recognition. A performance evaluation with ten experimental participants shows that the proposed scheme achieves a recall rate of each motion state of over 80% and an F-value of around 0.8.
ASJC Scopus subject areas
- Materials Science(all)