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Nuclear threat detection with mobile distributed sensor networks

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  • Dorit Hochbaum
  • Barak Fishbain

Abstract

The ability to track illicit radioactive source in an urban environment is critical in national security applications. To this end, two modes of operation are common: positioning individual portal monitors, and deploying a network of distributed sensors. We address here the use of multiple detectors, mounted on moving vehicles, for the purpose of detecting nuclear threats. An example scenario is that of multiple taxi cabs each carrying a detector. The detectors’ positions are known in real-time as these are continuously reported from GPS data. The level of detected risk is then reported from each detector at each position. The problem is to delineate the presence of a potentially dangerous source and its approximate location by identifying a small area that has an elevated concentration of reported risk. This problem of using spatially deployed mobile detector networks to identify and locate risks is modeled and formulated here. The problem is shown to be solvable in polynomial time and with a combinatorial network flow algorithm. The efficiency of the algorithm enable its use in real time, and in areas containing a large number of deployed detectors. A simulation study, that takes into account false-positive and false-negatives reports from individual sensors, demonstrates the effectiveness of the algorithm in using the sensor network’s detection capabilities. Copyright The Author(s) 2011

Suggested Citation

  • Dorit Hochbaum & Barak Fishbain, 2011. "Nuclear threat detection with mobile distributed sensor networks," Annals of Operations Research, Springer, vol. 187(1), pages 45-63, July.
  • Handle: RePEc:spr:annopr:v:187:y:2011:i:1:p:45-63:10.1007/s10479-009-0643-z
    DOI: 10.1007/s10479-009-0643-z
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    References listed on IDEAS

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    1. Dorit S. Hochbaum, 2008. "The Pseudoflow Algorithm: A New Algorithm for the Maximum-Flow Problem," Operations Research, INFORMS, vol. 56(4), pages 992-1009, August.
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    Cited by:

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    2. Baykal-Gürsoy, Melike & Duan, Zhe & Poor, H. Vincent & Garnaev, Andrey, 2014. "Infrastructure security games," European Journal of Operational Research, Elsevier, vol. 239(2), pages 469-478.
    3. Sushil Gupta & Martin K. Starr & Reza Zanjirani Farahani & Mahsa Mahboob Ghodsi, 2020. "Prevention of Terrorism–An Assessment of Prior POM Work and Future Potentials," Production and Operations Management, Production and Operations Management Society, vol. 29(7), pages 1789-1815, July.
    4. Yan, Xihong & Nie, Xiaofeng, 2016. "Optimal placement of multiple types of detectors under a small vessel attack threat to port security," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 71-94.
    5. Ling Tang & Shuai Wang & Kaijian He & Shouyang Wang, 2015. "A novel mode-characteristic-based decomposition ensemble model for nuclear energy consumption forecasting," Annals of Operations Research, Springer, vol. 234(1), pages 111-132, November.

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