TY - GEN
T1 - Wi-Fi fingerprint based indoor localization without indoor space measurement
AU - Jiang, Zhiping
AU - Zhao, Jizhong
AU - Han, Jinsong
AU - Tang, Shaojie
AU - Zhao, Jing
AU - Xi, Wei
PY - 2013
Y1 - 2013
N2 - Numerous indoor localization techniques have been proposed recently to meet the intensive demand for location-based service. Fingerprint-based approach is one of most popular and inexpensive solution. In terms of constructing the fingerprint database, there have to be a synchronized measurement for both indoor space(eg by labor-intensive site-survey or sensor-based crowd sensing) and fingerprint space, by this means the fingerprints database is established. It is the indoor space measurement hinders the usability of fingerprint-based localization system. In this work, we propose a sensor-free crowds ensing indoor localization scheme, protocol. The main contribution of our protocol is that we don't need indoor space measurement. Floor plan and RSS samples temporal sequence is the only requirement. The core of our method is a graph matching based manifold alignment process, which automatically finds the best correspondence between floor plan and wireless fingerprint transition structure. With no more need of indoor space measurement, the system deployment complexity and cost are significantly reduced. We implement our protocol at AP-end and deploy it in.
AB - Numerous indoor localization techniques have been proposed recently to meet the intensive demand for location-based service. Fingerprint-based approach is one of most popular and inexpensive solution. In terms of constructing the fingerprint database, there have to be a synchronized measurement for both indoor space(eg by labor-intensive site-survey or sensor-based crowd sensing) and fingerprint space, by this means the fingerprints database is established. It is the indoor space measurement hinders the usability of fingerprint-based localization system. In this work, we propose a sensor-free crowds ensing indoor localization scheme, protocol. The main contribution of our protocol is that we don't need indoor space measurement. Floor plan and RSS samples temporal sequence is the only requirement. The core of our method is a graph matching based manifold alignment process, which automatically finds the best correspondence between floor plan and wireless fingerprint transition structure. With no more need of indoor space measurement, the system deployment complexity and cost are significantly reduced. We implement our protocol at AP-end and deploy it in.
UR - https://www.scopus.com/pages/publications/84893282772
U2 - 10.1109/MASS.2013.84
DO - 10.1109/MASS.2013.84
M3 - Conference contribution
AN - SCOPUS:84893282772
SN - 9780768551043
T3 - Proceedings - IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems, MASS 2013
SP - 384
EP - 392
BT - Proceedings - IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems, MASS 2013
T2 - 10th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems, MASS 2013
Y2 - 14 October 2013 through 16 October 2013
ER -