The paper describes algorithms required to enable the crowd sourcing of indoor building maps, i.e., where GPS is not available. Nevertheless to enable crowd sourcing we use the 3-axis accelerometers and the 3-axis magnetometers available in many smart phones and the piezometer in a Nike running shoe. Volunteers carry the sensors while walking around in buildings, and use some application on their smart phone to send the data to a mapping server. We present the algorithms to obtain walking trajectories from the data by dead reckoning, and to estimate indoor maps with multiple walking trajectories. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Xuan, Y., Sengupta, R., & Fallah, Y. (2012). Crowd sourcing indoor maps with mobile sensors. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 73 LNICST, pp. 125–136). Springer Verlag. https://doi.org/10.1007/978-3-642-29154-8_11
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