Advertisement

Diffusion Distance-Based Predictive Tracking for Continuous Objects in Industrial Wireless Sensor Networks

  • Li Liu
  • Guangjie Han
  • Jiawei Shen
  • Wenbo Zhang
  • Yuxin Liu
Article
  • 84 Downloads

Abstract

In an industrial production process, the leakage of continuous objects poses a serious threat to production safety. In this paper, a diffusion distance-based predictive tracking algorithm is proposed for industrial wireless sensor networks (IWSNs), aiming to timely track the boundary of a continuous object after the occurrence of a leak. Based on the assumption that the motion of the continuous object follows an appropriate diffusion model, sensor nodes are able to capture environmental parameters for establishing the mathematical expression of the model locally. Through building up the relation of diffusion radius with time, each node predicts diffusion scope of the continuous object at different times and makes a judgment about whether it is suitable to be a boundary node. Moreover, to achieve high energy-efficiency, a sleep/wake cycle is introduced to involve a small number of nodes in the process of tracking, while the rest of nodes stay idle until an object approaches. Finally, a cluster-based competitive mechanism is proposed for reporting the location of boundary nodes. Simulation results demonstrated that our proposal is able to track the diffusion of continuous objects with high energy-efficiency.

Keywords

Predictive tracking Continuous objects Adiabatic diffusion Industrial wireless sensor networks 

Notes

Acknowledgments

The study was supported by the Qing Lan Project, the National Natural Science Foundation of China (under Grant No. 61572172), the Fundamental Research Funds for the Central Universities (No. 2016B10714), Open fund of State Key Laboratory of Acoustics (no. SKLA201706), the Changzhou Sciences and Technology Program (No. CE20165023 and No. CE20160014), and the Six talent peaks project in Jiangsu Province (No. XYDXXJS-007).

References

  1. 1.
    Han G, Liu L, Jiang J, Shu L, Hancke G (2017) Analysis of Energy-Efficient connected target coverage algorithms for industrial wireless sensor networks. IEEE Trans Ind Inf 13(1):135–143CrossRefGoogle Scholar
  2. 2.
    Sheng Z, Mahapatra C, Zhu C, Leung VCM (2015) Recent advances in industrial wireless sensor networks toward efficient management in IoT. IEEE Access 3:622–637CrossRefGoogle Scholar
  3. 3.
    Qiu T, Chen N, Li K, Qiao D, Fu Z (2017) Heterogeneous ad hoc networks: architectures, advances and challenges. Ad Hoc Netw 55:143–152CrossRefGoogle Scholar
  4. 4.
    Hou L, BergmannNovel NW (2012) Industrial wireless sensor networks for machine condition monitoring and fault diagnosis. IEEE Trans Instrum Meas 61(10):2787–2798CrossRefGoogle Scholar
  5. 5.
    Jeschke S, Brecher C, Song H, Rawat D (2017) Industrial internet of things: cybermanufacturing systems. Springer, Cham, pp 1– 715Google Scholar
  6. 6.
    Zhang Y, Yu R, Yao W, Xie S, Xiao Y, Guizani M (2011) Home M2M networks: architectures, standards, and QoS improvement. IEEE Commun Mag 49(4):44–52CrossRefGoogle Scholar
  7. 7.
    Zhang Y, Yu R, Nekovee M, Liu Y, Xie S, Gjessing S (2012) Cognitive machine-to-machine communications: visions and potentials for the smart grid. IEEE Network Magazine 26(3):6– 13CrossRefGoogle Scholar
  8. 8.
    Somov A, Baranov A, Spirjakin D (2013) Deployment and evaluation of a wireless sensor network for methane leak detection. Sens Actuators A Phys 202:217–225CrossRefGoogle Scholar
  9. 9.
    Shinde S, Patil SB, Patil AJ (2012) Development of movable gas tanker leakage detection using wireless sensor network based on embedded system. International Journal of Engineering Research and Application 2:1180–1183Google Scholar
  10. 10.
    Han G, Shen J, Liu L, Qian A, Shu L (2016) TGM-COT: Energy-efficient continuous object tracking scheme with two-layer grid model in wireless sensor networks. Pers Ubiquit Comput 20(3):349–359CrossRefGoogle Scholar
  11. 11.
    Ramya K, Kumar KP, Rao VS (2012) A survey on target tracking techniques in wireless sensor networks. International Journal of Computer Science and Engineering Survey 3(4):93–108CrossRefGoogle Scholar
  12. 12.
    Han G, Dong Y, Guo H, Shu L, Wu D (2015) Cross-layer optimized routing in wireless sensor networks with duty-cycle and energy harvesting. Wirel Commun Mob Comput 15(16):1957–1981CrossRefGoogle Scholar
  13. 13.
    Li S, Qin Z, Song H (2016) A Temporal-Spatial method for group detection, locating and tracking. IEEE Access 4:4484– 4494CrossRefGoogle Scholar
  14. 14.
    Qiu T, Lv Y, Xia F, Chen N, Wan J, Tolba A (2016) ERGID: an efficient routing protocol for emergency response internet of things. J Netw Comput Appl 72:104–112CrossRefGoogle Scholar
  15. 15.
    Qiu T, Liu X, Feng L, Zhou Y, Zheng K (2016) An efficient tree-based self-organizing protocol for internet of things. IEEE Access 4:3535–3546CrossRefGoogle Scholar
  16. 16.
    Han G, Shen J, Liu L, Shu L (2016) BRTCO: a novel boundary recognition and tracking algorithm for continuous objects in wireless sensor networks. IEEE Syst J,  https://doi.org/10.1109/JSYST.2016.2593949
  17. 17.
    Hussain CS, Park MS, Bashir AK (2013) A collaborative scheme for boundary detection and tracking of continuous objects in WSNs. Intelligent Automation & Soft Computing 19(3):439– 456CrossRefGoogle Scholar
  18. 18.
    Wu X, Chen H, Wang Y, Shu L, Liu G (2016) BP Neural network based continuous objects distribution detection in WSNs. Wirel Netw 22(6):1917–1929CrossRefGoogle Scholar
  19. 19.
    Chauhdary SH, Lee J, Shah SC, Park MS (2012) EBCO-Efficient boundary detection and tracking continuous objects in WSNs. KSII Trans Internet Inf Syst 6(11):2901– 2919Google Scholar
  20. 20.
    Park S, Hong SW, Lee E, Kim SH, Crespi N (2016) Large-scale mobile phenomena monitoring with energy-efficiency in wireless sensor networks. Comput Netw 81:116–135CrossRefGoogle Scholar
  21. 21.
    Chang WR, Lin HT, Cheng ZZ (2008) CODA: A continuous object detection and tracking algorithm for wireless ad hoc sensor networks. In: Proceedings of the 5th IEEE consumer communications and networking conference, pp 168– 174Google Scholar
  22. 22.
    Kim JH, Kim KB, Chauhdary SH, Yang W, Park MS (2008) DEMOCO: Energy-Efficient detection and monitoring for continuous objects in wireless sensor networks. IEICE Trans Commun 91(11):3648–3656CrossRefGoogle Scholar
  23. 23.
    Hong SW, Ryu HY, Park S (2015) Reliable continuous object tracking with cost effectiveness in wireless sensor networks. In: Proceeding of the ubiquitous and furture networks, pp 672– 676Google Scholar
  24. 24.
    Park S, Park H, Lee E, Kim SH (2012) Reliable and flexible detection of large-scale phenomena on wireless sensor networks. IEEE Commun Lett 16(6):933–936CrossRefGoogle Scholar
  25. 25.
    Dunning LA, Kresman R (2013) Privacy preserving data sharing with anonymous id assignment. IEEE Trans Inf Forensics Secur 8(2):402–413CrossRefGoogle Scholar
  26. 26.
    Moragrega A, Close P, Ibars C (2015) Potential game for Energy-Efficient Rss-Based positioning in wireless sensor networks. IEEE J Sel Areas Commun 33(7):1394–1406CrossRefGoogle Scholar
  27. 27.
    Han G, Jiang J, Zhang C, Duong TQ, Guizani M, Karagiannidis G (2016) A survey on mobile anchors assisted localization in wireless sensor networks. IEEE Commun Surv Tutorials 18(3):2220–2243CrossRefGoogle Scholar
  28. 28.
    Liu X, Godbole A, Lu C (2015) Optimisation of dispersion parameters of Gaussian plume model for CO2 dispersion. Environ Sci Pollut Res 22(22):18288–18299CrossRefGoogle Scholar
  29. 29.
    Gourgue H, Aharoune A, Ihlal A (2015) Study of the air pollutants dispersion from several point sources using an improved Gaussian model. Journal of Materials and Environmental Science 6(6):1584–1591Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Internet of Things EngineeringHohai UniversityChangzhouChina
  2. 2.State Key Laboratory of AcousticsInstitute of Acoustics Chinese Academy of SciencesBeijingChina
  3. 3.School of Information Science and EngineeringShenyang Ligong UniversityShenyangChina
  4. 4.Jiangsu Xin Zhongtian Plastic Industry Co., Ltd.ChangzhouChina

Personalised recommendations