Model-Based Localization and Tracking Using Bluetooth Low-Energy Beacons
AbstractWe introduce a high precision localization and tracking method that makes use of cheap Bluetooth low-energy (BLE) beacons only. We track the position of a moving sensor by integrating highly unreliable and noisy BLE observations streaming from multiple locations. A novel aspect of our approach is the development of an observation model, specifically tailored for received signal strength indicator (RSSI) fingerprints: a combination based on the optimal transport model of Wasserstein distance. The tracking results of the entire system are compared with alternative baseline estimation methods, such as nearest neighboring fingerprints and an artificial neural network. Our results show that highly accurate estimation from noisy Bluetooth data is practically feasible with an observation model based on Wasserstein distance interpolation combined with the sequential Monte Carlo (SMC) method for tracking. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Daniş, F.S.; Cemgil, A.T. Model-Based Localization and Tracking Using Bluetooth Low-Energy Beacons. Sensors 2017, 17, 2484.
Daniş FS, Cemgil AT. Model-Based Localization and Tracking Using Bluetooth Low-Energy Beacons. Sensors. 2017; 17(11):2484.Chicago/Turabian Style
Daniş, F. S.; Cemgil, Ali T. 2017. "Model-Based Localization and Tracking Using Bluetooth Low-Energy Beacons." Sensors 17, no. 11: 2484.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.