Detection of moving radioactive sources using sensor networks

Stephens, Daniel L.; Peurrung, A.J.

doi:10.1109/tns.2004.834713

Cited by 80 publications

(44 citation statements)

References 6 publications

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“…For the detection of radioactive sources, a linear arrangement of detectors has been considered in Nemzek et al [2004], Brennan et al [2004], and Mielke et al [2005], and an analysis of sensor network s olutions has been carried out for a source moving in a linear path [Stephens and Peurrung 2004]. The detection of a point radioactive source using a sensor network is addressed in Sundaresan et al [2007], wherein sensor measurements are combined using a copula function that captures the sensor correlations.…”

Section: :5mentioning

confidence: 99%

“…In general, the area of detecting various radioactive sources using individual sensors has been well established in terms of both detection devices and detection methods [Knoll 2000;Nelson et al 2007], most of which are dedicated to single or co-located sensor systems. Recent advances in sensor network technologies, however, have opened up the potential for improved detection, as well as the estimation of source parameters, by utilizing measurements from multiple, geographically dispersed sensors; see, for example, [Brennan et al 2004;Gunatilaka et al 2007;Mielke et al 2005;Nemzek et al 2004;Stephens and Peurrung 2004;Sundaresan et al 2007] for this line of work.…”

Section: Introductionmentioning

confidence: 99%

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Identification of low-level point radioactive sources using a sensor network

Chin

Rao

Yau

et al. 2010

ACM Trans. Sen. Netw.

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Identification of a low-level point radioactive source amidst background radiation is achieved by a network of radiation sensors using a two-step approach. Based on measurements from three or more sensors, a geometric difference triangulation method or an N-sensor localization method is used to estimate the location and strength of the source. Then a sequential probability ratio test based on current measurements and estimated parameters is employed to finally decide: (1) the presence of a source with the estimated parameters, or (2) the absence of the source, or (3) the Author's address: J.-C. Chin: email: jcchin@cs.purdue.edu. c 2010 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by a contractor or affiliate of the U.S. Government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept., ACM, Inc., 2 Penn Plaza, Suite 701, New York, NY 10121-0701 USA, fax +1 ( insufficiency of measurements to make a decision. This method achieves specified levels of false alarm and missed detection probabilities, while ensuring a close-to-minimal number of measurements for reaching a decision. This method minimizes the ghost-source problem of current estimation methods, and achieves a lower false alarm rate compared with current detection methods. This method is tested and demonstrated using: (1) simulations, and (2) a test-bed that utilizes the scaling properties of point radioactive sources to emulate high intensity ones that cannot be easily and safely handled in laboratory experiments.

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Section: :5mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of low-level point radioactive sources using a sensor network

Chin

Rao

Yau

et al. 2010

ACM Trans. Sen. Netw.

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“…Wireless sensor networks can be deployed in various applications namely environmental monitoring e.g. volcano detection [2,3], distributed control system [4] , detection of radioactive sources [5], agricultural and farm management [6], and computing platform for tomorrows' internet [7] .…”

Section: Introductionmentioning

confidence: 99%

Algorithm Based on One's Complement for Fast Scalar Multiplication in ECC for Wireless Sensor Network

Shah

Huang

Sharma

2010

2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops

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Elliptic curve cryptography (ECC) is having good potential for wireless sensor network security due to its smaller key size and its high strength of security. But there is a room to reduce key calculation time to meet the potential applications in particular for wireless sensor networks. Scalar multiplication is the operation in elliptical curve cryptography which takes 80 % of key calculation time on wireless sensor network motes. This research proposes algorithm based on 1's complement subtraction to represent scalar in scalar multiplication which offer less Hamming weight and will remarkably improve the computational efficiency of scalar multiplication.

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“…Distributed Sensor Networks (DSN) are frequently considered in support of this goal (Brennan et al 2004(Brennan et al , 2005Cunningham 1995;Nemzek et al 2004;Stephens and Peurrung 2004). Nemzek et al examine the signal-to-noise behavior that arises in the simple combination of data from networked radiation sensors and conclude that, for real-life scenarios, the individual portal monitors may be equivalent to, or better than, networked sensors.…”

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confidence: 99%

“…Naturally, this makes them impractical for use in real-life scenarios. Moreover, these methods do not directly lead to improved performance in terms of detection efficiency and reduction in false detection rate (Stephens and Peurrung 2004).…”

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confidence: 99%

Nuclear threat detection with mobile distributed sensor networks

Hochbaum

Fishbain

2009

Ann Oper Res

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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.

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Detection of moving radioactive sources using sensor networks

Cited by 80 publications

References 6 publications

Identification of low-level point radioactive sources using a sensor network

Identification of low-level point radioactive sources using a sensor network

Algorithm Based on One's Complement for Fast Scalar Multiplication in ECC for Wireless Sensor Network

Nuclear threat detection with mobile distributed sensor networks

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