This paper presents an indoor positioning system (IPS) by using fuzzy estimation technique. The research aims to design an IPS with high stability, high accuracy and high reliability. The received signal strengths (RSS) sensed by ZigBee wireless sensors were used to estimate the object’s position. All studies were experimented at a 10x10 square meters’ indoor field. In all experiments, 361 positions (features) were estimated. From the experimental results shown, the fuzzy positioning technique proposed has the high accurate estimation even RSS signals are unstable. It is also clearly found that the positioning accuracy could be greatly improved when more wireless sensors are used in IPS.
Published in | Journal of Electrical and Electronic Engineering (Volume 4, Issue 5) |
DOI | 10.11648/j.jeee.20160405.12 |
Page(s) | 97-102 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2016. Published by Science Publishing Group |
Indoor Positioning System, Fuzzy, ZigBee Wireless Sensor
[1] | E. Kaplan and C. Hegarty, Understanding GPS: Principles and Applicatons, 2nd ed. Norwood, MA: Artech House, 2006. |
[2] | C. C. Lin, M. J. Chiu, C. C. Hsiao, R. G. Lee, and Y. S. Tsai, “Wireless health care service system for elderly with dementia,” IEEE Trans. Inf. Technol. Biomed., pp. 696-704, 2006. |
[3] | M. Leblang, S. J. Dunham, and F. Pappalardi, “HMS scott ring laser gyro navigator integration,” Proceedings of OCEANS 2003, vol. 1, pp. 538-543, 2003. |
[4] | J. P. Yang, The Applications of Artificial Intelligence Technique in the Signal Characteristics’ Analysis, Ph.D. Thesis, I-Shou University, 2012. |
[5] | A. Kotanen, M. Hannikainen, H. Leppakoski, T. D. Hamalainen, “Positioning with IEEE 802.11b wireless LAN,” In the Proceedings of 14th IEEE Proceedings on Personal, Indoor and Mobile Radio Communications, Beijing, China, pp. 2218–2222, 2003. |
[6] | Y. B. Xu, M. Zhou, L. Ma, “Hybrid FCM/ANN indoor location method in WLAN environment,” In the Proceedings of IEEE Youth Conference on Information, Computing and Telecommunications, Beijing, China, pp. 475–478, 2009. |
[7] | V. Honkavirta, T. Perala, S. Ali-Loytty, R. Piche, “A comparative survey of WLAN location fingerprinting methods,” In the Proceedings of 6th Workshop on Positioning, Navigation and Communication (WPNC’09), Hannover, Germany, pp. 243–251, 2009. |
[8] | M. Y. Umair, K. V. Ramana, D. K. Yang, “An enhanced K-Nearest Neighbor algorithm for indoor positioning systems in a WLAN,” 2014 IEEE Computers, Communications and Its Applications, pp. 19-23, January 20, 2014. |
[9] | K. F. S. Wong, I. W. Tsang, V. Cheung, S. H. G. Chan, J. T. Kwok, “Position estimation for wireless sensor networks,” In the Proceedings of IEEE Global Telecommunications Conference, MO, USA, pp. 2772–2776, 2005. |
[10] | S. Aomumpai, K. Kondee, C. Prommak, K. Kaemarungsi, “Optimal placement of reference nodes for wireless indoor positioning systems,” 11th International Conference on Electrical Engineering, Electronics, Computer, Telecommunications and Information Technology. Paper no. 6839894, 2014. |
[11] | P. Bahl V. N. Padmanabhan, “RADAR: An in-building RF-based user location and tracking system,” In the Proceedings of INFOCOM 2000, Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, Tel Aviv, Israel, pp. 775-784, 2000. |
[12] | H. D. Chon, S. Jun, H. Jung, S. W. An, “Using RFID for accurate positioning,” Journal of Global Positioning Systems, vol. 3, pp. 32–39. 2004. |
[13] | H. L. Ding, W. W. Y. Ng, P. P. K. Chan, D. L. Wu, X. L. Chen, D. S. Yeung, “RFID indoor positioning using RBFNN with L-GEM,” In the Proceedings of IEEE 2010 International Conference on Machine Learning and Cybernetics, Qingdao, China, pp. 1147–1152, 2010. |
[14] | A. K. M. M. Hossain, W. S. Soh, “A comprehensive study of Bluetooth signal parameters for localization,” In the Proceedings of 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’07), Athens, Greece, pp. 1-5, 2007. |
[15] | F. Subhan, H. Hasbullah, A. Rozyyev, S. T. Bakhsh, “Indoor positioning in Bluetooth networks using fingerprinting and lateration approach,” In the Proceedings of 2011 International Conference on Information Science and Applications (ICISA), Jeju Island, Korea, pp. 1-9, 2001. |
[16] | W. P. Chen, X. F. Meng, “A cooperative localization scheme for Zigbee-based wireless sensor networks,” In the Proceedings of 14th IEEE International Conference on Networks, Singapore, pp. 1-5, 2006. |
[17] | G. Goncalo, S. Helena, “Indoor location system using ZigBee technology,” In the Proceedings of Third International Conference on Sensor Technologies and Applications, Athens/Glyfada, Greece, pp. 152-157, 2009. |
[18] | B. Kim, W. Bong, Y. C. Kim, “Indoor localization for Wi-Fi devices by cross-monitoring AP and weighted triangulation,” In the Proceedings of IEEE Consumer Communications and Networking Conference (CCNC), NV, U.S.A., pp. 933-936, 2011. |
[19] | Y. Mo, Z. Z. Zhang, Y. Lu, G. Agha, “A novel technique for human traffic based radio map updating in Wi-Fi indoor positioning systems,” KSII Transactions on Internet and Information Systems, vol. 9, no. 5, pp. 1881-1903, 2015. |
[20] | X. F. Jiang, C. J. Mike Liang, K. F. Chen, B. Zhang, J. Hsu, J. Liu, B. Cao, F. Zhao, “Design and evaluation of a wireless magnetic-based proximity detection platform for indoor applications,” In the Proceedings of 11th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN/SPOTS), Beijing, China, pp. 221-231, 2012. |
[21] | J. Hightower, G. Borriello, “Location sensing techniques,” Technical Report UW CSE 2001-07-30, Department of Computer Science and Engineering, University of Washington, 2001. |
[22] | K. Kaemarungsi, P. Krishnamurthy, “Properties of indoor received signal strength for WLAN location fingerprinting,” In the Proceedings of 1st Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous ’04), MA, USA, pp. 14-23, 2004. |
[23] | D. Focken, R. Stiefelhagen, “Towards vision-based 3-D people tracking in a smart room,” In the Proceedings of 4th IEEE Intl Conference on Multimodal Interfaces, PA, USA, pp. 400-405, 2002. |
[24] | S. Merat, W. Almuhtadi, “Wireless network channel quality estimation inside reactor building using RSSI measurement of wireless sensor network,” In the Proceedings of Canadian Conference on Electrical and Computer Engineering, Calgary, AB, Canada, pp. 339-341, 2009. |
[25] | H. C. Chen, Y. J. Chen, C. Y. Chen, S. M. T. Wang, J. P. Yang, R. C. Hwang, “A new indoor positioning technique based on neural network,” Advanced Science Letters, vol. 19, no. 7, pp. 2029-2033, 2013. |
[26] | C. Y. Chen, Y. J. Chen, Y. C. Weng, S. W. Chen, R. C. Hwang, “The sectored antenna array indoor positioning system with neural networks”, Automation, Control and Intelligent Systems, vol. 4, no. 2, pp. 21-27, 2016. |
[27] | L. X. Wang, A Course in Fuzzy Systems and Control, Prentice-Hall, Englewood Cliffs, NJ, 1997. |
[28] | H. X. Li and H. B. Gatland, "Conventional fuzzy control and its enhancement", IEEE Trans. on Systems, Man, Cybern., Part B, vol. 26, No. 5, pp. 791-797, 1996. |
[29] | Y. Yang, C. Zhou, J. Ren, “Model reference adaptive robust fuzzy control for ship steering autopilot with uncertain non-linear systems”, Applied Soft Computing, vol. 3 No. 4, pp. 305–316, 2003. |
[30] | D. Adrian, Allyson, “Fuzzy logic's diffusion in the study of business, the social sciences, philosophy, and medicine”, 2000 Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS, pp. 178-182, 2000. |
[31] | A. Corona Nakamura, R. Ruelas, D. Andina, B. Ojeda-Magaña, “A review of benefits of neuro-fuzzy systems applied in medicine”, The 9th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings, vol. 1, pp. 344-349, 2005. |
[32] | T. Margarita, “A distributed adaptive neuro-fuzzy network for chaotic time series prediction”, Cybernetics and Information Technologies, vol. 15, No. 1, pp. 24-33, 2015. |
[33] | M. Leandro, G. Fernando, B. Rosangela, “Stock market volatility prediction using possibilistic fuzzy modeling”, 2015 Latin-America Congress on Computational Intelligence, LA-CCI 2015, March 17, 2016, 2015. |
APA Style
Chih-Yung Chen, Yu-Ju Chen, Shen-Whan Chen, Chi-Yen Shen, Rey-Chue Hwang. (2016). A Fuzzy Indoor Positioning System with ZigBee Wireless Sensors. Journal of Electrical and Electronic Engineering, 4(5), 97-102. https://doi.org/10.11648/j.jeee.20160405.12
ACS Style
Chih-Yung Chen; Yu-Ju Chen; Shen-Whan Chen; Chi-Yen Shen; Rey-Chue Hwang. A Fuzzy Indoor Positioning System with ZigBee Wireless Sensors. J. Electr. Electron. Eng. 2016, 4(5), 97-102. doi: 10.11648/j.jeee.20160405.12
AMA Style
Chih-Yung Chen, Yu-Ju Chen, Shen-Whan Chen, Chi-Yen Shen, Rey-Chue Hwang. A Fuzzy Indoor Positioning System with ZigBee Wireless Sensors. J Electr Electron Eng. 2016;4(5):97-102. doi: 10.11648/j.jeee.20160405.12
@article{10.11648/j.jeee.20160405.12, author = {Chih-Yung Chen and Yu-Ju Chen and Shen-Whan Chen and Chi-Yen Shen and Rey-Chue Hwang}, title = {A Fuzzy Indoor Positioning System with ZigBee Wireless Sensors}, journal = {Journal of Electrical and Electronic Engineering}, volume = {4}, number = {5}, pages = {97-102}, doi = {10.11648/j.jeee.20160405.12}, url = {https://doi.org/10.11648/j.jeee.20160405.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20160405.12}, abstract = {This paper presents an indoor positioning system (IPS) by using fuzzy estimation technique. The research aims to design an IPS with high stability, high accuracy and high reliability. The received signal strengths (RSS) sensed by ZigBee wireless sensors were used to estimate the object’s position. All studies were experimented at a 10x10 square meters’ indoor field. In all experiments, 361 positions (features) were estimated. From the experimental results shown, the fuzzy positioning technique proposed has the high accurate estimation even RSS signals are unstable. It is also clearly found that the positioning accuracy could be greatly improved when more wireless sensors are used in IPS.}, year = {2016} }
TY - JOUR T1 - A Fuzzy Indoor Positioning System with ZigBee Wireless Sensors AU - Chih-Yung Chen AU - Yu-Ju Chen AU - Shen-Whan Chen AU - Chi-Yen Shen AU - Rey-Chue Hwang Y1 - 2016/10/20 PY - 2016 N1 - https://doi.org/10.11648/j.jeee.20160405.12 DO - 10.11648/j.jeee.20160405.12 T2 - Journal of Electrical and Electronic Engineering JF - Journal of Electrical and Electronic Engineering JO - Journal of Electrical and Electronic Engineering SP - 97 EP - 102 PB - Science Publishing Group SN - 2329-1605 UR - https://doi.org/10.11648/j.jeee.20160405.12 AB - This paper presents an indoor positioning system (IPS) by using fuzzy estimation technique. The research aims to design an IPS with high stability, high accuracy and high reliability. The received signal strengths (RSS) sensed by ZigBee wireless sensors were used to estimate the object’s position. All studies were experimented at a 10x10 square meters’ indoor field. In all experiments, 361 positions (features) were estimated. From the experimental results shown, the fuzzy positioning technique proposed has the high accurate estimation even RSS signals are unstable. It is also clearly found that the positioning accuracy could be greatly improved when more wireless sensors are used in IPS. VL - 4 IS - 5 ER -