Skip to main content
SpringerLink
Log in

Accurate Identification of Low-Level Radiation Sources with Crowd-Sensing Networks

  • Conference paper
  • First Online:
Book cover Big Data Computing and Communications (BigCom 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9784))

Included in the following conference series:

  • 1521 Accesses

Abstract

The use of crowd-sensing networks is a promising and low-cost way for identifying low-level radiation sources, which is greatly important for the security protection of modern cities. However, it is challenging to identify radiation sources based on the inaccurate crowd-sensing measurements with unknown sensor efficiency, due to uncontrollable nature of users. Existing methods mainly concentrate on wireless sensor network, where the sensor efficiency is available. To address this problem, inspired by EM (Expectation Maximization) method, we propose an iterative truthful-source identification algorithm. It alternately iterates between sensor efficiency estimation and truthful-source identification, gradually improving the identification accuracy. The extensive simulations and theoretical analysis show that, our method can converge into the maximum likelihood of crowd-sensing measurements, and achieve much higher identification accuracy than the existing methods.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bickel, P.J., Li, B.: Mathematical statistics. Test 15 (1977)

    Google Scholar 

  2. Chin, J.C., Rao, N.S.V., Yau, D.K.Y., Shankar, M., Yang, Y., Hou, J.C., Srivathsan, S., Iyengar, S.: Identification of low-level point radioactive sources using a sensor network. ACM Trans. Sens. Netw. 7(3), 1–35 (2010)

    Article  Google Scholar 

  3. Chin, J.C., Yau, D.K.Y., Rao, N.S.V.: Efficient and robust localization of multiple radiation sources in complex environments. In: ICDCS, pp. 780–789. IEEE (2011)

    Google Scholar 

  4. Chin, J.C., Yau, D.K.Y., Rao, N.S.V., Yang, Y., Ma, C.Y.T., Shankar, M.: Accurate localization of low-level radioactive source under noise and measurement errors. In: SenSys (2008)

    Google Scholar 

  5. Dempster, A., Laird, N., Rubin, D.: Maximum likelihood from incomplete data via the em algorithm. J. R. Stat. Soc. Ser. B 39(1), 1–38 (1977)

    MathSciNet  MATH  Google Scholar 

  6. Ganti, R.K., Ye, F., Lei, H.: Mobile crowdsensing: current state and future challenges. IEEE Commun. Mag. 49(11), 32–39 (2011)

    Article  Google Scholar 

  7. Hasenfratz, D., Saukh, O., Sturzenegger, S., Thiele, L.: Participatory air pollution monitoring using smartphones. In: International Workshop on Mobile Sensing, Beijing, China (2012)

    Google Scholar 

  8. Jeremic, A., Nehorai, A.: Landmine detection and localization using chemical sensor array processing. IEEE Trans. Sig. Process. 48(5), 1295–1305 (2000)

    Article  Google Scholar 

  9. Lane, N.D., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., Campbell, A.T.: A survey of mobile phone sensing. IEEE Commun. Mag. 48(9), 140–150 (2010)

    Article  Google Scholar 

  10. Ma, H., Zhao, D., Yuan, P.: Opportunities in mobile crowd sensing. IEEE Commun. Mag. 52(8), 29–35 (2014)

    Article  Google Scholar 

  11. Nehorai, A., Porat, B., Paldi, E.: Detection and localization of vapor-emitting sources. IEEE Trans. Sig. Process. 43(1), 243–253 (1995)

    Article  Google Scholar 

  12. Rao, N.S.V., Shankar, M., Chin, J.C., Yau, D.K.Y., Srivathsan, S., Iyengar, S.S., Yang, Y., Hou, J.C.: Identification of low-level point radiation sources using a sensor network. In: IPSN, pp. 493–504. IEEE (2008)

    Google Scholar 

  13. Rao, N.S., Shankar, M., Chin, J.C., Yau, D.K., Ma, C.Y., Yang, Y., Hou, J.C., Xu, X., Sahni, S.: Localization under random measurements with application to radiation sources. In: International Conference on Information Fusion, pp. 1–8. IEEE (2008)

    Google Scholar 

  14. Sundaresan, A., Varshney, P.K., Rao, N.S.: Distributed detection of a nuclear radioactive source using fusion of correlated decisions. In: International Conference on Information Fusion, pp. 1–7. IEEE (2007)

    Google Scholar 

  15. Wu, C.F.J.: On the convergence properties of the em algorithm. Ann. Stat. 11(1), 95–103 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  16. Xiang, C., Yang, P., Tian, C., Zhang, L., Lin, H., Xiao, F., Zhang, M., Liu, Y.: CARM: crowd-sensing accurate outdoor RSS maps with error-prone smartphone measurements. IEEE Trans. Mobile Comput. pp. 99 (2016)

    Google Scholar 

  17. Zhao, T., Nehorai, A.: Detecting and estimating biochemical dispersion of a moving source in a semi infinite medium. IEEE Trans. Sig. Process. 54(6), 2213–2225 (2006)

    Article  Google Scholar 

Download references

Acknowledgment

This research is partially supported by Jiangsu Distinguished Young Scholar Awards, NSF China under Grants No. 61502520, 61272487, 61232018, and BK20150030.

Author information

Authors and Affiliations

  1. Logistic Engineering University, Chongqing, China

    Chaocan Xiang, Zhendong Yang & Xin Shen

  2. University of Science and Technology of China, Hefei, China

    Panlong Yang

  3. PLA University of Science and Technology, Nanjing, China

    Wanru Xu

Authors
  1. Chaocan Xiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Panlong Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wanru Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhendong Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xin Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Panlong Yang .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of N. Carolina at Charlotte, Charlotte, North Carolina, USA

    Yu Wang

  2. Northeastern University, College of Information Science and Engineering, Shenyang, Liaoning, China

    Ge Yu

  3. Department of Electrical & Computer Engineering, Rutgers University, Piscataway, New Jersey, USA

    Yanyong Zhang

  4. Department of Electrical and Computer Engineering, University of Houston Department of Engineering, Houston, Texas, USA

    Zhu Han

  5. College of Information Science and Engineering, Northeastern University, Shenyang , Liaoning, China

    Guoren Wang

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Xiang, C., Yang, P., Xu, W., Yang, Z., Shen, X. (2016). Accurate Identification of Low-Level Radiation Sources with Crowd-Sensing Networks. In: Wang, Y., Yu, G., Zhang, Y., Han, Z., Wang, G. (eds) Big Data Computing and Communications. BigCom 2016. Lecture Notes in Computer Science(), vol 9784. Springer, Cham. https://doi.org/10.1007/978-3-319-42553-5_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-42553-5_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42552-8

  • Online ISBN: 978-3-319-42553-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation