Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings
Abstract
:1. Introduction
2. Materials and Methods
2.1. Model of Indoor Localization
2.2. Fingerprinting Localization
- The stage configuration environment. At this stage, the power signals of all the known active beacons are measured in pre-planned locations. The information collected is stored in a database with reference to the local coordinate space (assigned to specific rooms) or global coordinate space (assigned to a building).
- Step positioning. At this stage, the signal power measurements made over the receiver are compared with the information stored in the database by means of an algorithm. The k-nearest neighbors algorithm is used [58].
2.2.1. K-Nearest Neighbors
2.2.2. Fuzzy Logic Type-1
2.2.3. Fuzzy Logic Type-2
2.3. Evaluation
3. Experiments and Results
3.1. Experiment Setting
3.2. Results of Fingerprinting Localization
3.3. Real-World Experiment
3.4. Evaluation
3.5. Evaluation
4. Concluding Remarks
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Appendix B
Appendix C
Linguistic Variables | Membership Function Variable Values |
---|---|
Very Small Distance | 0.0→0.0→2.5 |
Small Distance | 0.0→2.5→5.0 |
Medium Distance | 2.5→5.0→7.5 |
Large Distance | 5.0→7.5→10.0 |
Very Large Distance | 7.5→10.0→10.0 |
Linguistic Variables | Membership Function Variable Values |
---|---|
Very Small Weight | 0.0 |
Small Weight | 2.5 |
Medium Weight | 5.0 |
Large Weight | 7.5 |
Very Large Weight | 10.0 |
Linguistic Variables | Membership Function Variable Values |
---|---|
Very Small Distance | 0.0→0.0→2.5 |
Small Distance | 0.0→2.5→5.0 |
Medium Distance | 2.5→5.0→7.5 |
Large Distance | 5.0→7.5→10.0 |
Very Large Distance | 7.5→10.0→10.0 |
Linguistic Variables | Membership Function Variable Values |
---|---|
RSSI-Close | −35.0→−28.0→−20.0 |
RSSI-Near | −66.0→−44.5→−31.0 |
RSSI-Far | −90.0→−75.0→−60.5 |
Linguistic Variables | Membership Function Variable Values |
---|---|
Very Small Weight | 0.0 |
Small Weight | 2.5 |
Medium Weight | 5.0 |
Large Weight | 7.5 |
Very Large Weight | 10.0 |
Linguistic Variables | Upper Membership Function | Lower Membership Function |
---|---|---|
Very Small Distance | 0.0→0.0→3.0 | 0.0→0.0→2.0 |
Small Distance | 0.0→2.5→5.5 | 0.5→2.5→4.5 |
Medium Distance | 2.0→5.0→8.0 | 3.0→5.0→7.0 |
Large Distance | 4.5→7.5→10.0 | 5.5→7.5→9.5 |
Very Large Distance | 7.0→10.0→10.0 | 8.0→10.0→10.0 |
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Method | Technology | Environment | Error in Meters | Error % |
---|---|---|---|---|
Segura et al. [17] | UWB | Room (6 m × 8 m) | 0.2 | N/A |
Zhang et al. [19] | GPS, UWB, MARG | Business center | 3.2 | N/A |
Sun et al. [21] | PDR | Atrium of Informatics Forum building (9.7 m × 5.94 m) | 1.96 | N/A |
Yang et al. [24] | Stereo Camera | Room (8 m × 8.4 m × 4 m) | 0.677 | N/A |
Qiu et al. [22] | Inertial/magnetic sensors, PDR | Room (approx. 20 m diameter, height 10 m), empty room | 2.59 | N/A |
Meliones et al. [25] | Inertial dead-reckoning, BLE beacon | Floor (1640 m2) | N/A | 2.53% |
Liu et al. [16] | Peak intensities of lights | Supermarket (1000 m2) | N/A | 0% |
Shopping mall (20 000 m2) | N/A | 1.7% | ||
Office building (800 m2) | N/A | 0% | ||
Großwindhager et al. [18] | UWB | Office room (4 m × 6 m) | 0.2 | N/A |
Zhou et al. [20] | Camera, PDR | Meeting room (16 m × 7.7 m) | 0.56 | N/A |
Xu et al. [29] | grid-based, WiFi | Office (780 m2) Lab (1200 m2) | 3.5m | N/A |
Wang et al. [27] | WiFi, PDR | Floor in China University of Mining and Technology | 4.99 | N/A |
Nguyen-Huu et al. [28] | PDR, WiFi fingerprint | Floor in Engineering building, Hallym University | 2.40 | N/A |
Patel et al. [30] | BLE, Mapping/Poi | Office floor (1200 m2) | 1.6 | N/A |
Proposed Method | BLE fingerprint, fuzzy logic | Floor (52.5m × 12.5 m) | 0.43 | N/A |
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AL-Madani, B.; Orujov, F.; Maskeliūnas, R.; Damaševičius, R.; Venčkauskas, A. Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings. Sensors 2019, 19, 2114. https://doi.org/10.3390/s19092114
AL-Madani B, Orujov F, Maskeliūnas R, Damaševičius R, Venčkauskas A. Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings. Sensors. 2019; 19(9):2114. https://doi.org/10.3390/s19092114
Chicago/Turabian StyleAL-Madani, Basem, Farid Orujov, Rytis Maskeliūnas, Robertas Damaševičius, and Algimantas Venčkauskas. 2019. "Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings" Sensors 19, no. 9: 2114. https://doi.org/10.3390/s19092114
APA StyleAL-Madani, B., Orujov, F., Maskeliūnas, R., Damaševičius, R., & Venčkauskas, A. (2019). Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings. Sensors, 19(9), 2114. https://doi.org/10.3390/s19092114