Efficient Wireless Sensor Network for Radiation Detection in Nuclear Sites

Authors

Abstract

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 main sources of electric power and a lot of 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 a novel and efficient ML-based RDWSNs that utilizes millimeter waves (mmWaves) to cope with future networks 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 radiations using software applications installed in these mobiles. Moreover, a battery aware TS (BA-TS) algorithm is proposed to forward the sensed radiation levels to fusion decision center efficiently. BA-TS reflects the remaining battery of each mobile device to prolong the network lifetime. Simulation results ensure the efficiency of the proposed BA-TS algorithm regards throughput and network lifetime over TS and exhaustive search method.

Author Biography

Sherief Hashima, Engineering Dept, Nuclear Research center, Egyptian Atomic Energy Authority Inshas Cairo 13759 Egypt

Sherief Hashima received his B.Sc. and M.Sc. degrees in Electronics and Communication Engineering (ECE), with class of honors, in 2004, 2010 from Tanta and Menoufiya University, Egypt, respectively. He obtained his Ph.D degree from Egypt-Japan University of Science & Technology (EJUST), Alexandria, EGYPT at 2014. He is a postdoctoral researcher, computational learning theory team, RIKEN AIP, Japan since July 2019. He is working as assistant professor at the Engineering and scientific equipment Department, Nuclear Research Center (NRC), Egyptian Atomic Energy Authority (EAEA), Egypt since 2014. From Jan-June 2018, he was a visiting researcher at Center for Japan-Egypt Cooperation in Science and Technology, Kyushu University. He is a technical committee member in many international conferences and a reviewer in many international conferences, journals and transactions. His research interests include wireless communications, machine learning, online learning, 5G, B5G, and 6G systems, image processing, millimeter waves, nuclear instrumentation, and internet of things.

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Published

2024-04-19

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Section

Applied Informatics