Demo: IMU−Aided Magneto−Inductive Localization
T. E. Abrudan‚ Zhuoling Xiao‚ A. Markham and N. Trigoni
Abstract
In this work, we propose an infrastructure-based indoor localization system that exploits the predictable spatio-temporal features of a local magnetic field. The system also relies on inertial data in order to map the environment and track the user's location. Additionally, WiFi access points may be used to improve the performance.
Address
Berlin‚ Germany
Book Title
Microsoft Indoor Localization Competition‚ at the 13th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2014)
Copyright
ACM
Month
13–17 Apr.
Year
2014