Localization for visually impaired people in dynamically changing environments with unexpected hazards and obstacles is a current need. Many techniques have been discussed in the literature with respect to location-based services and techniques used for the positioning of devices. Time difference of arrival (TDOA), time of arrival (TOA) and received signal strength (RSS) have been widely used for the positioning but narrow band signals such as Bluetooth cannot efficiently utilize TDOA or TOA. Received signal strength indicator (RSSI) to measure RSS, has been found to be more reliable. RSSI measurement estimations depend heavily on the environmental interference. RSSI measurement estimations of Bluetooth systems can be improved either by improving the existing methodologies used to implement them or by using fusion techniques that employ Kalman filters to combine more than one RSSI method to improve the results significantly. This paper focuses on improving the existing methodology of measuring RSSI by proposing a new method using trilateration for localization of Bluetooth devices for visually impaired people. To validate the new method, class 2 Bluetooth devices (Blue Giga WT-12) were used with an evaluation board. The software required was developed in National Instruments LabView. The PCB was designed and manufactured as well. Experiments were then conducted, and surface plots of Bluetooth modules were obtained to show the signal interference and other environmental effects. Lastly, the results were discussed, and relevant conclusions were drawn.
References
[1]
Treuillet, S. and Royer, E. (2010) Outdoor/Indoor Vision-Based Localization for Blind Pedestrian Navigation Assistance. International Journal of Image and Graphics, 10, 481-496. https://doi.org/10.1142/S0219467810003937
[2]
Hollinger, K. (2016) O&M for Independent Living: Strategies for Teaching Orientation and Mobility to Older Adults. Journal of Visual Impairment & Blindness, 110, 33-39. https://doi.org/10.1177/0145482X1611000208
[3]
WHO (2007) Visual Impairment and Blindness: Fact Sheet.
http://www.who.int/mediacentre/factsheets/fs282/en
[4]
Golledge, R.G., Loomis, J.M., Klatzky, R., Flury, A. and Yang, X.-L. (1991) Designing a Personal Guidance System to Aid Navigation without Sight: Progress on the GIS Component. International Journal of Geographical Information Systems, 5, 373-395. https://doi.org/10.1080/02693799108927864
[5]
Halder, S. and Ghosal, A. (2014) Mobility-Assisted Localization Techniques in Wireless Sensor Networks: Issues, Challenges and Approaches. In: Koubaa, A. and Khelil, A., Eds., Cooperative Robots and Sensor Networks 2014, Vol. 554, Springer, Berlin, 43-64. https://doi.org/10.1007/978-3-642-55029-4_3
[6]
Paum, F., Erhardt, S., Weigel, R. and Koelpin, A. (2017) RSSI-Based Localization with Minimal Infrastructure Using Multivariate Statistic Techniques. IEEE Topical Conference on Wireless Sensors and Sensor Networks, Phoenix, 15-18 January 2017, 69-72.
[7]
Kowalik, R. and Kwasniewski, S. (2004) Navigator—A Talking GPS Receiver for the Blind. International Conference on Computers for Handicapped Persons, Paris, 7-9 July 2004, 446-449. https://doi.org/10.1007/978-3-540-27817-7_65
[8]
Loomis, J.M., Golledge, R.D. and Klatzky, R.L. (2001) GPS-Based Navigation Systems for the Visually Impaired. Lawrence Erlbaum Associates, Mahwah.
[9]
Helal, A., Moore, S.E. and Ramachandran, B. (2001) Drishti: An Integrated Navigation System for Visually Impaired and Disabled. Proceedings 5th International Symposium on Wearable Computers, Zurich, 8-9 October 2001, 149-156.
https://doi.org/10.1109/ISWC.2001.962119
[10]
Ran, L., Helal, S. and Moore, S. (2004) Drishti: An Integrated Indoor/Outdoor Blind Navigation System and Service. 2nd IEEE Annual Conference on Pervasive Computing and Communications, Orlando, 14-17 March 2004, 23-30.
https://doi.org/10.1109/PERCOM.2004.1276842
[11]
Na, J. (2006) The Blind Interactive Guide System Using RFID-Based Indoor Positioning System. In: Miesenberger, K., Klaus, J., Zagler, W.L. and Karshmer, A.I., Eds., Computers Helping People with Special Needs, Springer, Berlin, Heidelberg, 1298-1305. https://doi.org/10.1007/11788713_187
[12]
Kulyukin, V., Gharpure, C., Nicholson, J. and Pavithran, S. (2004) RFID in Robot-Assisted Indoor Navigation for the Visually Impaired. IEEE/RSJ International Conference on Intelligent Robots and Systems, Sendai, 28 September-2 October 2004, Vol. 2, 1979-1984.
[13]
Hesch, J.A. and Roumeliotis, S.I. (2007) An Indoor Localization Aid for the Visually Impaired. Proceedings 2007 IEEE International Conference on Robotics and Automation, Roma, 10-14 April 2007, 3545-3551.
https://doi.org/10.1109/ROBOT.2007.364021
[14]
Rueppel, U. and Stuebbe, K.M. (2008) BIM-Based Indoor-Emergency Navigation-System for Complex Buildings. Tsinghua Science and Technology, 13, 362-367.
https://doi.org/10.1016/S1007-0214(08)70175-5
[15]
Jeamwatthanachai, W., Wald, M. and Wills, G. (2017) Map Data Representation for Indoor Navigation by Blind People. International Journal of Chaotic Computing, 4, 70-78.
[16]
Wang, Q., Balasingham, I., Zhang, M. and Huang, X. (2011) Improving RSS-Based Ranging in LOS-NLOS Scenario Using GMMS. IEEE Communications Letters, 15, 1065-1067. https://doi.org/10.1109/LCOMM.2011.080811.111087
[17]
Farid, Z., Nordin, R. and Ismail, M. (2013) Recent Advances in Wireless Indoor Localization Techniques and System. Journal of Computer Networks and Communications, 2013, Article ID: 185138. https://doi.org/10.1155/2013/185138
[18]
Ahn, H. and Yu, W. (2009) Environmental-Adaptive RSSI-Based Indoor Localization. IEEE Transactions on Automation Science and Engineering, 6, 626-633.
https://doi.org/10.1109/TASE.2008.2009126
[19]
Kriz, P., Maly, F. and Kozel, T. (2016) Improving Indoor Localization Using Blue-Tooth Low Energy Beacons. Mobile Information Systems, 2016, Article ID: 2083094. https://doi.org/10.1155/2016/2083094
[20]
Dabrowski, A., Kardys, P. and Marciniak, T. (2005) Bluetooth Technology Applications Dedicated to Supporting Blind and Hearing as Well as Speech Handicapped People. 47th International Symposium ELMAR, Zadar, 8-10 June 2005, 295-298.
https://doi.org/10.1109/ELMAR.2005.193702
[21]
Altini, M., Brunelli, D., Farella, E. and Benini, L. (2010) Bluetooth Indoor Localization with Multiple Neural Networks. IEEE 5th International Symposium on Wireless Pervasive Computing, Modena, 5-7 May 2010, 295-300.
https://doi.org/10.1109/ISWPC.2010.5483748
[22]
Millar, S. (1994) Understanding and Representing Space: Theory and Evidence from Studies with Blind and Sighted Children. Oxford Scholarship Online.
https://doi.org/10.1093/acprof:oso/9780198521426.001.0001
[23]
Park, S. and Hashimoto, S. (2009) Autonomous Mobile Robot Navigation Using Passive RFID in Indoor Environment. IEEE Transactions on Industrial Electronics, 56, 2366-2373. https://doi.org/10.1109/TIE.2009.2013690
[24]
Willis, S. and Helal, S. (2004) A Passive RFID Information Grid for Location and Proximity Sensing for the Blind User. 295-300.
[25]
Maneesilp, J., Wang, C., Wu, H. and Tzeng, N. (2013) RFID Support for Accurate 3D Localization. IEEE Transactions on Computers, 62, 1447-1459.
https://doi.org/10.1109/TC.2012.83
[26]
Amemiya, T., Yamashita, J., Hirota, K. and Hirose, M. (2004) Virtual Leading Blocks for the Deaf-Blind: A Real-Time Way-Finder by Verbal-Nonverbal Hybrid Interface and High-Density RFID Tag Space. IEEE Virtual Reality 2004, Chicago, 27-31 March, 2004, 165-287. https://doi.org/10.1109/VR.2004.1310070
[27]
D’Atri, E., Medaglia, C.M., Serbanati, A., Ceipidor, U.B., Panizzi, E. and D’Atri, A. (2007) A System to Aid Blind People in the Mobility: A Usability Test and Its Results. Second International Conference on Systems, Sainte-Luce, 22-28 April 2007, 35-35. https://doi.org/10.1109/ICONS.2007.7
[28]
Chen, H. and Lin, K. (2011) An Improved Method for Free-Space Antenna-Factor Measurement by Using the Music Algorithm. IEEE Transactions on Electromagnetic Compatibility, 53, 274-282. https://doi.org/10.1109/TEMC.2010.2050775
[29]
Agarwal, K. and Chen, X. (2008) Applicability of Music-Type Imaging in Two-Dimensional Electromagnetic Inverse Problems. IEEE Transactions on Antennas and Propagation, 56, 3217-3223. https://doi.org/10.1109/TAP.2008.929434
[30]
Wong, K.T. and Zoltowski, M.D. (2000) Self-Initiating Music-Based Direction Finding in Underwater Acoustic Particle Velocity-Field Beamspace. IEEE Journal of Oceanic Engineering, 25, 262-273. https://doi.org/10.1109/48.838989
[31]
Henault, S., Antar, Y.M.M., Rajan, S., Inkol, R. and Wang, S. (2008) Impact of Mutual Coupling on Wideband Adcock Direction Finders. Canadian Conference on Electrical and Computer Engineering, Niagara Falls, 4-7 May 2008, 001327-001332.
https://doi.org/10.1109/CCECE.2008.4564755
[32]
Paul, A.S. and Wan, E.A. (2009) RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers. IEEE Journal of Selected Topics in Signal Processing, 3, 860-873. https://doi.org/10.1109/JSTSP.2009.2032309
[33]
Ahn, H. and Ko, K.H. (2009) Simple Pedestrian Localization Algorithms Based on Distributed Wireless Sensor Networks. IEEE Transactions on Industrial Electronics, 56, 4296-4302. https://doi.org/10.1109/TIE.2009.2017097
[34]
Ibrahim, M. and Youssef, M. (2012) Cellsense: An Accurate Energy-Efficient GSM Positioning System. IEEE Transactions on Vehicular Technology, 61, 286-296.
https://doi.org/10.1109/TVT.2011.2173771
[35]
Chen, Z., Zou, H., Jiang, H., Zhu, Q., Soh, Y. and Xie, L. (2015) Fusion of Wifi, Smartphone Sensors and Landmarks Using the Kalman Filter for Indoor Localization. Sensors, 15, 715-732. https://doi.org/10.3390/s150100715
[36]
Chen, Z., Zhu, Q. and Soh, Y.C. (2016) Smartphone Inertial Sensor-Based Indoor Localization and Tracking with Ibeacon Corrections. IEEE Transactions on Industrial Informatics, 12, 1540-1549. https://doi.org/10.1109/TII.2016.2579265
[37]
Danifis, F. and Cemgil, A. (2017) Model-Based Localization and Tracking Using Bluetooth Low-Energy Beacons. Sensors, 17, pii: E2484.
https://doi.org/10.3390/s17112484
[38]
Wu, K., Xiao, J., Yi, Y., Chen, D., Luo, X. and Ni, L.M. (2013) CSI-Based Indoor Localization. IEEE Transactions on Parallel and Distributed Systems, 24, 1300-1309.
https://doi.org/10.1109/TPDS.2012.214
[39]
Sahu, P.K., Wu, E.H. and Sahoo, J. (2013) Durt: Dual RSSI Trend Based Localization for Wireless Sensor Networks. IEEE Sensors Journal, 13, 3115-3123.
https://doi.org/10.1109/JSEN.2013.2257731
[40]
Chen, Y., Lymberopoulos, D., Liu, J. and Priyantha, B. (2013) Indoor Localization Using FM Signals. IEEE Transactions on Mobile Computing, 12, 1502-1517.
https://doi.org/10.1109/TMC.2013.58
[41]
Miller, B.A. and Bisdikian, C. (2000) Understanding and Representing Space: Theory and Evidence from Studies with Blind and Sighted Children. Prentice Hall, Upper Saddle River.
[42]
Cheung, K.C., Intille, S.S. and Larson, K. (2006) An Inexpensive Bluetooth-Based Indoor Positioning Hack.
[43]
Diaz, J.J.M., Maufies, R.d.A., Soares, R.B., Nakamura, E.F. and Figueiredo, C.M.S. (2010) Bluepass: An Indoor Bluetooth-Based Localization System for Mobile Applications. The IEEE Symposium on Computers and Communications, Riccione, 22-25 June 2010, 778-783. https://doi.org/10.1109/ISCC.2010.5546506
[44]
Hossain, A.K.M.M. and Soh, W. (2007) A Comprehensive Study of Bluetooth Signal Parameters for Localization. IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications, Athens, 3-7 September 2007, 1-5.
https://doi.org/10.1109/PIMRC.2007.4394215
[45]
Feldmann, S., Kyamakya, K., Zapater, A. and Lue, Z. (2003) An Indoor Bluetooth-Based Positioning System: Concept, Implementation and Experimental Evaluation. International Conference on Wireless Networks, Las Vegas, 23-26 June 2003, 109-113.
[46]
Li, D. and Wang, J. (2009) Research of Indoor Local Positioning Based on Bluetooth Technology. 5th International Conference on Wireless Communications, Networking and Mobile Computing, New York, 24-26 September 2009, 1-4.
https://doi.org/10.1109/WICOM.2009.5302300
[47]
Bohonos, S., Lee, A., Malik, A., Thai, C. and Manduchi, R. (2007) Universal Real-Time Navigational Assistance (URNA): An Urban Bluetooth Beacon for the Blind. In: Proceedings of the 1st ACM SIGMOBILE International Workshop on Systems and Networking Support for Healthcare and Assisted Living Environments, ACM, New York, 83-88. https://doi.org/10.1145/1248054.1248080
[48]
Liu, X., Makino, H., Kobayashi, S. and Maeda, Y. (2007) Design of an Indoor Self-Positioning System for the Visually Impaired-Simulation with RFID and Bluetooth in a Visible Light Communication System. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Lyon, 22-26 August 2007, 1655-1658. https://doi.org/10.1109/IEMBS.2007.4352625
[49]
Pathak, O., Palaskar, P., Palkar, R. and Tawari, M. (2014) Wifi Indoor Positioning System Based on RSSI Measurements from Wifi Access Points—A Tri-Lateration Approach. International Journal of Scientific and Engineering Research, 5, 1234-1238.
