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Face-Based Mobile Target Tracking Technique in Wireless Sensor Network

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Abstract

A prediction-based method is presented to track mobile object and its location in a sensor network area. In recent years, energy consumption and high accuracy target tracking have been a challenge in wireless sensor network. A number of applications have been used to reduce energy depletion by involving only a few number of sensor nodes to contribute in communication, sensing for target tracking, and transaction. In this study, the Face-based Target Tracking Technique (FTTT) is used to minimise energy depletion to extend the lifetime of sensor node as well as to track object accurately. FTTT combines prediction algorithm with face routing, which can produce accurate detection. At the beginning, sensor node in the border detects the object and elects Triangular sensor Nodes (TN) in the face structure which are the nearest to the object. The process is then continued with TNs tracking the Moving Object (MO) and predicting its next position by face routing structure. The next set of face-based structures will activate TN and offer continuous tracking of the MO. The simulation of the proposed technique are evaluated against the existing approach in terms of object tracking, object detection, speed monitoring as well as energy consumption. The results of FTTT show high accuracy of object detection with less energy consumption.

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References

  1. Hai-bo, Y., Ning, Q., & You-rong, C. (2009). An object tracking technique in wireless sensor network based on prediction. In International conference on communication software and networks, 2009. ICCSN’09 (pp. 3–8). IEEE.

  2. Alaybeyoglu, A., Erciyes, K., Kantarci, A., & Dagdeviren, O. (2010). Tracking fast moving targets in wireless sensor networks. IETE Technical Review, 27(1), 46–53.

    Article  Google Scholar 

  3. Alaybeyoglu, A., Kantarci, A., & Erciyes, K. (2010). A dynamic distributed tree based tracking algorithm for wireless sensor networks. In Recent trends in wireless and mobile networks (pp. 295–303). Berlin: Springer.

  4. Lin, C. Y., & Tseng, Y. C. (2004). Structures for in-network moving object tracking in wireless sensor networks. In First international conference on broadband networks, 2004. BroadNets 2004. Proceedings (pp. 718–727). IEEE.

  5. Lin, C. Y., Peng, W. C., & Tseng, Y. C. (2006). Efficient in-network moving object tracking in wireless sensor networks. IEEE Transactions on Mobile Computing, 5(8), 1044–1056.

    Article  Google Scholar 

  6. Yeong-Sung, F., & Hsu, Y. Y. (2010, June). An energy-efficient algorithm for object tracking in Wireless Sensor Networks. In 2010 IEEE international conference on wireless communications, networking and information security (pp. 424–430). IEEE.

  7. Liu, B. H., Ke, W. C., Tsai, C. H., & Tsai, M. J. (2008). Constructing a message-pruning tree with minimum cost for tracking moving objects in wireless sensor networks is NP-complete and an enhanced data aggregation structure. IEEE Transactions on Computers, 57(6), 849–863.

    Article  MathSciNet  Google Scholar 

  8. Hsu, J. M., Chen, C. C., & Li, C. C. (2011, June). Short-term prediction-based optimistic object tracking strategy in wireless sensor networks. In 2011 fifth international conference on innovative mobile and internet services in ubiquitous computing (IMIS) (pp. 78–85). IEEE.

  9. Wang, G., Bhuiyan, M. Z. A., Cao, J., & Wu, J. (2014). Detecting movements of a target using face tracking in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 25(4), 939–949.

    Article  Google Scholar 

  10. Bhuiyan, M. Z. A., Wang, G., & Wu, J. (2009). Target tracking with monitor and backup sensors in wireless sensor networks. In 2009 Proceedings of 18th international conference on computer communications and networks (pp. 1–6). IEEE.

  11. Bhuiyan, M. Z. A., Wang, G. J., Zhang, L., & Peng, Y. (2010). Prediction-based energy-efficient target tracking protocol in wireless sensor networks. Journal of Central South University of Technology, 17(2), 340–348.

    Article  Google Scholar 

  12. Chen, T. S., Liao, W. H., Huang, M. D., & Tsai, H. W. (2005, November). Dynamic object tracking in wireless sensor networks. In 2005 13th IEEE international conference on networks, 2005 jointly held with the 2005 IEEE 7th Malaysia international conference on communication (Vol. 1). IEEE.

  13. Kulathumani, V., Arora, A., Demirbas, M., & Sridharan, M. (2007, January). Trail: A distance sensitive WSN service for distributed object tracking. In European conference on wireless sensor networks (pp. 83–100). Berlin: Springer.

  14. Bose, P., Morin, P., Stojmenovi, I., & Urrutia, J. (2001). Routing with guaranteed delivery in ad hoc wireless networks. Wireless Networks, 7(6), 609–616.

    Article  Google Scholar 

  15. Tsai, H. W., Chu, C. P., & Chen, T. S. (2007). Mobile object tracking in wireless sensor networks. Computer Communications, 30(8), 1811–1825.

    Article  Google Scholar 

  16. Xu, Y., Winter, J., & Lee, W. C. (2004). Dual prediction-based reporting for object tracking sensor networks. In The first annual international conference on mobile and ubiquitous systems: networking and services, 2004. MOBIQUITOUS 2004 (pp. 154–163). IEEE.

  17. Mohanoor, A. B., Radhakrishnan, S., & Sarangan, V. (2009). Online energy aware routing in wireless networks. Ad Hoc Networks, 7(5), 918–931.

    Article  Google Scholar 

  18. Intanagonwiwat, C., Govindan, R., Estrin, D., Heidemann, J., & Silva, F. (2003). Directed diffusion for wireless sensor networking. IEEE/ACM Transactions on Networking (ToN), 11(1), 2–16.

    Article  Google Scholar 

  19. Naderan, M., Dehghan, M., Pedram, H., & Hakami, V. (2012). Survey of mobile object tracking protocols in wireless sensor networks: A networkcentric perspective. International Journal of Ad Hoc and Ubiquitous Computing, 11(1), 34–63.

    Article  Google Scholar 

  20. Huang, Q., Lu, C., & Roman, G. C. (2004). Reliable mobicast via face-aware routing. In INFOCOM 2004. twenty-third annual joint conference of the IEEE computer and communications societies (Vol. 3, pp. 2108–2118). IEEE.

  21. Karp, B., & Kung, H. T. (2000). GPSR: Greedy perimeter stateless routing for wireless networks. In Proceedings of the 6th annual international conference on mobile computing and networking (pp. 243–254). ACM.

  22. Chui, C. K., & Chen, G. (2009). Kalman filtering with real-time applications. Springer series in Information Sciences (4th ed.). New York, NY: Springer.

  23. Haseltine, E. L., & Rawlings, J. B. (2005). Critical evaluation of extended Kalman filtering and moving-horizon estimation. Industrial & Engineering Chemistry Research, 44(8), 2451–2460.

    Article  Google Scholar 

  24. Tsukamoto, K., Ueda, H., Tamura, H., Kawahara, K., & Oie, Y. (2009). Design of wireless sensor network for multi-point surveillance of a moving target based on the relationship between tracking probability and sensor density. In Consumer communications and networking conference, 2009. CCNC 2009. 6th IEEE (pp. 1–5). IEEE.

  25. Mahgoub, I., & Ilyas, M. (2016). Sensor network protocols. Boca Raton: CRC Press.

    Google Scholar 

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Authors and Affiliations

  1. Universiti Putra Malaysia Fakulti Kejuruteraan, Serdang, Selangor, Malaysia

    Khalid Ali, Mohd Fadlee A. Rasid, Aduwati Sali & Borhanuddin Ali

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  1. Khalid Ali
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  2. Mohd Fadlee A. Rasid
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  3. Aduwati Sali
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  4. Borhanuddin Ali
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Correspondence to Khalid Ali.

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Ali, K., Rasid, M.F.A., Sali, A. et al. Face-Based Mobile Target Tracking Technique in Wireless Sensor Network. Wireless Pers Commun 111, 1853–1870 (2020). https://doi.org/10.1007/s11277-019-06961-3

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  • DOI: https://doi.org/10.1007/s11277-019-06961-3

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