Abstract

Nuclear newcomers need to verify the support infrastructure development keeps steady with the power plant construction and radioactive materials transportation. European power reactor's (EPR) spent fuel (SF) had been chosen in this paper for newcomers to determine the SF levels. Radioactive materials are causing harm to the environment, people, and property. These materials may be subject to terrorism, particularly during transportations. Therefore, solutions for the safety of storing and transporting radioactive materials will be proposed in this paper. Recently, the world is suffering from a new type of terrorist—known as “Lone Wolves”—which can attack these materials. Lone wolves harmful attack detection is extremely difficult at any attack stage. Existing surveillance systems are weak to counter the lone wolves, where they respond after the happening of the incident. Therefore, this paper proposed a design for Lone Wolves counter-system (LWCS) based on deep learning and assisted by internet of things to prevent these attacks. Also, an embedded system solution will be proposed based on existing infrastructure networks. The proposed embedded system can monitor and track the radioactive materials during storing and transportation in real-time. Simulation results for the proposed system will show improved performance in the transport of radioactive materials.

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