Research and Implementation of Bluetooth Indoor Auto-tracking System

Authors

  • Yen-Jen Chen Dept. of Electronics Eng., Ming Chi University of Technology, Taiwan, R.O.C.
  • Kai-Wen Zheng Dept. of Electronics Eng., Ming Chi University of Technology, Taiwan, R.O.C.

DOI:

https://doi.org/10.14738/tnc.66.5808

Keywords:

Bluetooth, Auto-tracking System, RSSI, Indoor Location

Abstract

In recent years, outdoor positioning technology has been widely used and indoor positioning technology has gradually matured.  Relevant applications such as: Indoor Location Based Service, Ambient Assistant Living, Indoor Navigation, Location Based Advertising, and the like have begun to show up in daily life and bring people with diversity and rich service content. The proposed study focuses on the research of real-time indoor dynamic positioning and dynamic tracking related mechanisms and algorithms, and uses the “microcontroller module” and “Bluetooth communication module” to actually detect the operational mechanism of the Bluetooth dynamic positioning system. This prototype system uses the smart phone as the locator of the traced person, named tracee (a new word created in this paper). The three-wheeled carrier acts as the tracer's body. On the locator, the processor is used to dynamically calculate the dynamic positioning of the tracee, and the calculated positioning result is transmitted to the tracer through the Bluetooth. The tracer calculates the distance and orientation, and then controls the axle motor so that the three-wheeled carrier closely follows the smart phone. Although many self-propelled vehicles have been sold on the market at present, and most of the follow-up signal uses infrared rays, ultrasonic waves, or Wi-Fi to complete the tracking action. However, the first two signals often require the tracee to carry an additional signal transmission device so as to assist in tracking. Due to the current popularity of mobile phones, although Wi-Fi and Bluetooth chips are already installed on the phone, yet the power consumption of Wi-Fi is still much higher than that of the Bluetooth. Therefore, in this study, Bluetooth was used to complete the indoor positioning system.  Bluetooth belongs to 2.4GHz wireless technology; when using the Bluetooth signal for tracking, the signal strength is likely to cause many noises due to shielding, signal diffraction, or reflection, resulting in a deviation between the calculated transmission distance and the actual distance. The purpose of this study is to design a prototype of an Indoor Automatic Tracking System (hereafter named IATS) and explorer how to reduce the Bluetooth signal strength deviation so as to improve the accuracy of positioning is the main object of this study.

References

(1) Mautz Rainer, Indoor Positioning Technologies, 2012

(2) Ishida, S., Tagashira, S., Arakawa, Y. and Fukuda, A., On-demand Indoor Location-Based Service Using Ad-hoc Wireless Positioning Network, 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems, New York, NY, 2015: p. 1005-1013.

(3) Chen, H., and Cui, L., DS-MMAC: A delay-sensitive multi-channel MAC protocol for Ambient Assistant Living systems, in China Communications, vol. 13, no. 5 ,May 2016: p. 38-46,

(4) Caruso, D., Sanfourche, M., Le Besnerais, G., and Vissière, D., Infrastructureless indoor navigation with a hybrid magneto-inertial and depth sensor system, 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Alcala de Henares, Spain, 2016:

p. 1-8.

(5) Liu, H., Darabi, H., Banerjee, P., and Liu, J., Survey of Wireless Indoor Positioning Techniques and Systems, in IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 37, no. 6, Nov. 2007: p. 1067-1080.

(6) Perera et al, A. A. G. A. K., Ads-In Site: Location based advertising framework with social network analyzer, 2014 14th International Conference on Advances in ICT for Emerging Regions (ICTer), Colombo, 2014: p. 116-123.

(7) Djaja-Josko, V., and Kolakowski, J., A new transmission scheme for wireless synchronization and clock deviations reduction in UWB positioning system, 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Alcala de Henares, 2016: p. 1-6.

(8) Djaja-Josko, V., and Kolakowski, J., A new method for wireless synchronization and TDOA deviation reduction in UWB positioning system, 2016 21st International Conference on Microwave, Radar and Wireless Communications (MIKON), Krakow, 2016: p. 1-4.

(9) Xie, Y., Janssen, G. J. M., and Veen, A. J., A practical clock synchronization algorithm for UWB positioning systems, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, 2016: p. 3891-3895.

(10) Chen, H. and H. Vun, C., Compressive sensing techniques for UWB indoor positioning applications, 2015 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, 2015: p. 231-232.

(11) Piccinni, G., Avitabile, G., Coviello, G., and Talarico, C., Distributed amplifier design for UWB positioning systems using the gm over id methodology, 2016 13th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD), Lisbon, 2016: p. 1-4.

(12) Luo, Y., and Law, C. L., Indoor Positioning Using UWB-IR Signals in the Presence of Dense Multipath with Path Overlapping, in IEEE Transactions on Wireless Communications, vol. 11, no. 10, October 2012: p. 3734-3743.

(13) Khyam, M. O., Alam, M. J., Lambert, A. J., Garratt and M. R. Pickering, M. A., High-Precision OFDM-Based Multiple Ultrasonic Transducer Positioning Using a Robust Optimization Approach, in IEEE

Sensors Journal, vol. 16, no. 13 July1, 2016: p. 5325-5336.

(14) Kranz, M., Fischer, C., and Schmidt, A., A comparative study of DECT and WLAN signals for indoor localization, 2010 IEEE International Conference on Pervasive Computing and Communications (PerCom), Mannheim, 2010: p. 235-243.

(15) Chung-Hsin, Liu., and Jian-Yun, Lo., The study for the WLAN with ZigBee positioning system, The 6th International Conference on Networked Computing and Advanced Information Management, Seoul, 2010: p. 520-525.

(16) Hieu, D. C., Van Tuan, Le., Thanh Hieu, Nguyen., Masuda, A., Rabarijaona, V. H., and Shimamoto, S., Low power consumption Intelligent Local Avoided Collision (iLAC) MAC protocol for WLAN, 2012 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Ho Chi Minh City, 2012: p. 000001-000006.

(17) Nair et al, K., Optimizing power consumption in iot based wireless sensor networks using Bluetooth Low Energy, 2015 International Conference on Green Computing and Internet of Things (ICGCIoT), Noida, 2015: p. 589-593.

(18) Pei, L., Chen, R., Liu, J., Tenhunen, T., Kuusniemi, H., and Chen, Y., Inquiry-Based Bluetooth Indoor Positioning via RSSI Probability Distributions, 2010 Second International Conference on Advances in Satellite and Space Communications, Athens, 2010: p. 151-156.

(19) Varshney, V., Goel, R. K., and Qadeer, M. A., Indoor positioning system using Wi-Fi & Bluetooth Low Energy technology, 2016 Thirteenth International Conference on Wireless and Optical Communications Networks (WOCN), Hyderabad, 2016: p. 1-6.

(20) Dickinson, P., Cielniak, G., Szymanezyk, O., and Mannion, M., Indoor positioning of shoppers using a network of Bluetooth Low Energy beacons, 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Alcala de Henares, 2016: p. 1-8.

(21) Varshney, V., Goel, R. K., and Qadeer, M. A., Indoor positioning system using Wi-Fi & Bluetooth Low Energy technology, 2016 Thirteenth International Conference on Wireless and Optical Communications Networks (WOCN), Hyderabad, 2016: p. 1-6.

(22) Jian, S., Yongling, F., Lin, T., and Shengguang, L., A Survey and Application of Indoor Positioning Based on Scene Classification Optimization, 2015 IEEE 12th Intl Conf on Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom), Beijing, 2015: p. 1558-1562.

(23) Al Nuaimi, K., and Kamel, H., A survey of indoor positioning systems and algorithms, 2011 International Conference on Innovations in Information Technology, Abu Dhabi, 2011: p. 185-190.

Downloads

Published

2019-01-01

How to Cite

Chen, Y.-J., & Zheng, K.-W. (2019). Research and Implementation of Bluetooth Indoor Auto-tracking System. Discoveries in Agriculture and Food Sciences, 6(6), 76. https://doi.org/10.14738/tnc.66.5808