Identifying anomalous nuclear radioactive sources using Poisson kriging and mobile sensor networks.

Nuclear security is a critical concept for public health, counter-terrorism efforts, and national security. Nuclear radioactive materials should be monitored and secured in near real-time to reduce potential danger of malicious usage. However, several challenges have arose to detect the anomalous ra...

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Main Authors: Jifu Zhao, Zhe Zhang, Clair J Sullivan
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0216131
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spelling doaj-63f2ba298030431f9f703ed19bc029c02021-03-03T20:42:18ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-01145e021613110.1371/journal.pone.0216131Identifying anomalous nuclear radioactive sources using Poisson kriging and mobile sensor networks.Jifu ZhaoZhe ZhangClair J SullivanNuclear security is a critical concept for public health, counter-terrorism efforts, and national security. Nuclear radioactive materials should be monitored and secured in near real-time to reduce potential danger of malicious usage. However, several challenges have arose to detect the anomalous radioactive source in a large geographical area. Radiation naturally occurs in the environment. Therefore, a non-zero level of radiation will always exist with or without an anomalous radioactive source present. Additionally, radiation data contain high levels of uncertainty, meaning that the measured radiation value is significantly affected by the velocity of the detector and background noise. In this article, we propose an innovative approach to detect anomalous radiation source using mobile sensor networks combined with a Poisson kriging technique. We validate our results using several experiments with simulated radioactive sources. As results, the accuracy of the model is extremely high when the source intensity is high or the anomalous source is close enough to the detector.https://doi.org/10.1371/journal.pone.0216131
collection DOAJ
language English
format Article
sources DOAJ
author Jifu Zhao
Zhe Zhang
Clair J Sullivan
spellingShingle Jifu Zhao
Zhe Zhang
Clair J Sullivan
Identifying anomalous nuclear radioactive sources using Poisson kriging and mobile sensor networks.
PLoS ONE
author_facet Jifu Zhao
Zhe Zhang
Clair J Sullivan
author_sort Jifu Zhao
title Identifying anomalous nuclear radioactive sources using Poisson kriging and mobile sensor networks.
title_short Identifying anomalous nuclear radioactive sources using Poisson kriging and mobile sensor networks.
title_full Identifying anomalous nuclear radioactive sources using Poisson kriging and mobile sensor networks.
title_fullStr Identifying anomalous nuclear radioactive sources using Poisson kriging and mobile sensor networks.
title_full_unstemmed Identifying anomalous nuclear radioactive sources using Poisson kriging and mobile sensor networks.
title_sort identifying anomalous nuclear radioactive sources using poisson kriging and mobile sensor networks.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2019-01-01
description Nuclear security is a critical concept for public health, counter-terrorism efforts, and national security. Nuclear radioactive materials should be monitored and secured in near real-time to reduce potential danger of malicious usage. However, several challenges have arose to detect the anomalous radioactive source in a large geographical area. Radiation naturally occurs in the environment. Therefore, a non-zero level of radiation will always exist with or without an anomalous radioactive source present. Additionally, radiation data contain high levels of uncertainty, meaning that the measured radiation value is significantly affected by the velocity of the detector and background noise. In this article, we propose an innovative approach to detect anomalous radiation source using mobile sensor networks combined with a Poisson kriging technique. We validate our results using several experiments with simulated radioactive sources. As results, the accuracy of the model is extremely high when the source intensity is high or the anomalous source is close enough to the detector.
url https://doi.org/10.1371/journal.pone.0216131
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