Smartphone Distance Estimation Based on RSSI-Fuzzy Classification Approach
comunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/43662
comunitat-uji-handle3:10234/159451
comunitat-uji-handle4:
INVESTIGACIONMetadata
Title
Smartphone Distance Estimation Based on RSSI-Fuzzy Classification ApproachDate
2021-06-15Publisher
Institute of Electrical and Electronics Engineers; IEEEISBN
9781728196442Bibliographic citation
P. Pascacio, S. Casteleyn and J. Torres-Sospedra, "Smartphone Distance Estimation Based on RSSI-Fuzzy Classification Approach," 2021 International Conference on Localization and GNSS (ICL-GNSS), 2021, pp. 1-6, doi: 10.1109/ICL-GNSS51451.2021.9452226.Type
info:eu-repo/semantics/conferenceObjectPublisher version
https://ieeexplore.ieee.org/xpl/conhome/9452123/proceedingVersion
info:eu-repo/semantics/submittedVersionSubject
Abstract
Positioning people indoors has known an exponential growth in the last few years, especially thanks to Bluetooth Low Energy (BLE) technology and the Received Signal Strength Indicator (RSSI) technique. This approach ... [+]
Positioning people indoors has known an exponential growth in the last few years, especially thanks to Bluetooth Low Energy (BLE) technology and the Received Signal Strength Indicator (RSSI) technique. This approach is available in wearable devices, is easy to implement and has energy consumption advantages. However, the relative distance calculation is inaccurate, as the strength of BLE signals significantly fluctuates in indoor environments. Typical coping mechanisms, such as path-loss propagation models, require mathematical modeling and time-consuming calibration, that depend on the environment. In this paper, we propose a novel distance estimator based on RSSI-fuzzy classification of the BLE signals. Fuzzy-logic improves the robustness and accuracy of RSSI-based estimators, does not require an explicit propagation model and is easy and intuitive to (graphically) tune (using basic statistical analysis). The estimator's suitability and the feasibility to provide an easy implementation were experimentally demonstrated in two scenarios with real-world data. [-]
Description
Ponencia presentada en 2021 International Conference on Localization and GNSS (ICL-GNSS), 1-3 June 2021
Funder Name
European Union’s Horizon 2020 Research | Gobierno de España
Project code
PTQ2018-009981