Efficient Wireless Sensor Network for Radiation Detection in Nuclear Sites

• Autorzy: Hashima Sherief , Mahmoud Imbab

Identyfikatory

DOI

10.24425/ijet.2021.135961

• Języki publikacji: EN

Abstrakty

EN

Due to the severe damages of nuclear accidents, there is still an urgent need to develop efficient radiation detection wireless sensor networks (RDWSNs) that precisely monitor irregular radioactivity. It should take actions that mitigate the severe costs of accidental radiation leakage, especially around nuclear sites that are the primary sources of electric power and many health and industrial applications. Recently, leveraging machine learning (ML) algorithms to RDWSNs is a promising solution due to its several pros, such as online learning and self-decision making. This paper addresses novel and efficient ML-based RDWSNs that utilize millimeter waves (mmWaves) to meet future network requirements. Specifically, we leverage an online learning multi-armed bandit (MAB) algorithm called Thomson sampling (TS) to a 5G enabled RDWSN to efficiently forward the measured radiation levels of the distributed radiation sensors within the monitoring area. The utilized sensor nodes are lightweight smart radiation sensors that are mounted on mobile devices and measure radiation levels using software applications installed in these mobiles. Moreover, a battery aware TS (BATS) algorithm is proposed to efficiently forward the sensed radiation levels to the fusion decision center. BA-TS reflects the remaining battery of each mobile device to prolong the network lifetime. Simulation results ensure the proposed BA-TS algorithm’s efficiency regards throughput and network lifetime over TS and exhaustive search method.

Słowa kluczowe

EN

wireless sensor networks; WSN; radiation detection; multi-armed bandit (MAB); Thomson sampling; network lifetime

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2021
• Tom: Vol. 67, No. 2
• Strony: 175--180
• Opis fizyczny: Bibliogr. 19 poz., rys., schem., wykr.

Twórcy

autor

Hashima Sherief

• Engineering Dept., Nuclear Research Center, Egyptian Atomic Energy Authority, Cairo 13759, Egypt

autor

Mahmoud Imbab

• Radiation Engineering Dept., National Center of Radiation Research and Technology (NCRRT) Egyptian Atomic Energy Authority, Cairo, Egypt

Bibliografia

• [1] R. Elhabyan, W. Shi and M. St-Hilaire, ”Coverage protocols for wireless sensor networks: Review and future directions,” Journal of Communications and Networks,21, (1), 45-60, Feb. 2019, DOI: 10.1109/JCN.2019.000005.
• [2] X. Ge, Q. Han, X. Zhang, L. Ding and F. Yang, ”Distributed Event-Triggered Estimation Over Sensor Networks: A Survey,” IEEE Transactions on Cybernetics, 50 (3), 1306-1320, March 2020, DOI: 10.1109/TCYB.2019.2917179.
• [3] International Atomic Energy Authority (IAEA) accident reports available online, https://www.iaea.org/topics/accident-reports.
• [4] R. R. Kumar, L. Macwin and R. Rathna, ”Nuclear radiation detection using Wireless Sensor Network,” 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), Coimbatore, 2015, pp. 1-4, DOI: 10.1109/ICIIECS.2015.7192790.
• [5] R. Dersch, Primary and secondary measurements of 222Rn, Journal of Applied Radiation and Isotopes, 60, Issues 2–4,2004, Pages 387-39, 2004, DOI: 10.1016/j.apradiso.2003.11.046.
• [6] Drew, Christina Grace, Deirdre Silbernagel, Susan Hemmings, Erin Smith, Alan Griffith, William Takaro, Tim Faustman, Elaine, ”Nuclear Waste Transportation: Case Studies of Identifying Stakeholder Risk Information Needs”. Environmental health perspectives. 111. 263-72, DOI: 10.1289/ehp.5203.
• [7] Manar, M.K., Mohamed, S., Hashima, S., Imbaby, I.M., Amal-Eldin, M., Nesreen, I. “Hardware Implementation for Pileup Correction Algorithms in Gamma Ray Spectroscopy. International Journal of Computer Applications, 176, 43-48, 2017. DOI: 10.5120/ijca2017915634
• [8] Bensaleh, Mohammed Saida, Raoudha Hadj kacem, Yessine Abid, Mohamed. ”Wireless Sensor Network Design Methodologies: A Survey”. Journal of Sensors, pp. 1-13, 2020. DOI: 10.1155/2020/9592836.
• [9] B. Xing, R. Ding and J. Wang, ”Design of Wireless Sensor Network for Protection of X-Ray Detection,” 2013 6th International Conference on Intelligent Networks and Intelligent Systems (ICINIS), Shenyang, 2013, pp. 282-285, DOI: 10.1109/ICINIS.2013.79.
• [10] M. Altayeb, M. Mekki, O. Abdallah, A. B. Mustafa and S. Abdalla, ”Automobile and fixed wireless sensor network for radiation detection,” 2015 International Conference on Computing, Control, Networking, Electronics and Embedded Systems Engineering (ICCNEEE), Khartoum, 2015, pp. 199-202, DOI: 10.1109/ICCNEEE.2015.7381361.
• [11] C. Liu, P. -. Drouin, G. St-Jean, M. Déziel and D. Waller, ”Wireless Radiation Sensor Network with directional radiation detectors,” IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), Seattle, WA, pp. 1-6, 2014. DOI: 10.1109/NSSMIC.2014.7431111.
• [12] Jianxin Sun, ”Radiation detection using mobile sensor networks”, PhD thesis, University of Delaware, spring 2016.
• [13] Ding, Fei Zhang, Deng-yin Wang, Wanping Lei, Zhenzhong. (2018). ”A Low Complexity Active Sensing and Inspection System for Monitoring of Moveable Radiation Environments”. Journal of Sensors. 2018. 1-9. 10.1155/2018/8096012.
• [14] M. S. Muktadir, S. Islam and A. R. Alam Chowdhury, ”Development of a Wireless Safety System Based on Multiple Radiation Detector for Nuclear Facilities,” International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), Dhaka, Bangladesh, pp. 539-542, 2019. DOI: 10.1109/ICREST.2019.8644312.
• [15] Vasile Buruiana, Mihaela Oprea. A Microcontroller-Based Radiation Monitoring and Warning System. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012. DOI: 10.1007/978-3-642-33412-2_39.
• [16] Barbarán, Javier Díaz, a Esteve, Iňaki Rubio, Bartolomé. RadMote: a mobile framework for radiation monitoring in nuclear power plants, 2007.
• [17] S. Duraisamy, G. K. Pugalendhi and P. Balaji, ”Reducing energy consumption of wireless sensor networks using rules and extreme learning machine algorithm,” The Journal of Engineering, vol. 2019, no. 9, pp. 5443-5448, 9, 2019, DOI: 10.1049/joe.2018.5288.
• [18] Thompson, William R. ”On the Likelihood That One Unknown Probability Exceeds Another in View of the Evidence of Two Samples.” Biometrika 25, no. 3/4, 1933. DOI: 10.2307/2332286.
• [19] F. Wilhelmi, C. Cano, G. Neu, B. Bellalta, A. Jonsson, and S. Barrachina-Munoz, “Collaborative spatial reuse in wireless networks via selfish multi-armed bandits,” Ad Hoc Networks, vol. 88, pp. 129–141, 10, 2017. DOI: 10.1016/j.adhoc.2019.01.006.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).