Device-independent cellular-based indoor location tracking using deep learning

2021 ◽  
pp. 101420
Author(s):  
Hamada Rizk ◽  
Moustafa Abbas ◽  
Moustafa Youssef
Keyword(s):  
Deep Learning ◽  
Location Tracking ◽  
Indoor Location

Indoor Location Tracking Using Inertial Navigation Sensors and Radio Beacons

2008 ◽  
pp. 325-340 ◽  
Author(s):  
Pedro Coronel ◽  
Simeon Furrer ◽  
Wolfgang Schott ◽  
Beat Weiss
Keyword(s):  
Inertial Navigation ◽  
Location Tracking ◽  
Indoor Location

scholarly journals Smartphone-Based Indoor Pedestrian Tracking Using Geo-Magnetic Observations

2013 ◽  
Vol 9 (2) ◽  
pp. 123-137 ◽  
Author(s):  
Sungnam Lee ◽  
Yohan Chon ◽  
Hojung Cha
Keyword(s):  
Environmental Changes ◽  
Tracking System ◽  
Magnetic Sensors ◽  
Location Based Services ◽  
Location Tracking ◽  
Magnetic Fluctuations ◽  
Pedestrian Tracking ◽  
Estimation Model ◽  
Indoor Location ◽  
Extensive Evaluation

With the widespread use of smartphones, the use of location-based services (LBS) with smartphones has become an active research issue. The accurate measurement of user location is necessary to provide LBS. While outdoor locations are easily obtained with GPS, indoor location information is difficult to acquire. Previous work on indoor location tracking systems often relied on infrastructures that are influenced by environmental changes and temporal differences. Several studies have proposed infrastructure-less systems that are independent of the surroundings, but these works generally required non-trivial computation time or energy costs. In this paper, we propose an infrastructure-less pedestrian tracking system in indoor environments. The system uses accelerometers and magnetic sensors in smartphones without pre-installed infrastructure. We reduced the cumulative error of location tracking by geo-magnetic observations at corners and spots with magnetic fluctuations. In addition, we developed a robust estimation model that is tolerant to false positives, as well as a mobility model that reflects the characteristics of multiple sensors. Extensive evaluation in a real environment indicates that our system is accurate and cost-effective.

Sign in / Sign up

Export Citation Format

Share Document