Semnan University Press Journal of Modeling in Engineering 2008-4854 23 82 2025 09 23 Tracking and Exploring out-of-Control Radioactive Materials in Crowded Scenarios based on the Overlaying of Machine Vision System Images-Radiation Counting Map (Fast and Efficient Method) Tracking and Exploring out-of-Control Radioactive Materials in Crowded Scenarios based on the Overlaying of Machine Vision System Images-Radiation Counting Map (Fast and Efficient Method) 85 98 9698 10.22075/jme.2024.34640.2695 FA Amir Mohammad Beigzadeh Radiation Application Research School, NSTRI, Tehran, Iran Hadi Ardiny Radiation Application Research School, NSTRI, Tehran, Iran Journal Article 2024 07 02 The rapid expansion of nuclear technology on a global scale has heightened concerns regarding the significant risks posed by radioactive materials to both human societies and the environment. In environments characterized by high levels of traffic and congestion, the effective detection and tracking of out-of-control radioactive materials are paramount to ensuring the safety and security of individuals and communities. This study introduces an innovative and efficient method that integrates machine vision system images with radiation-counting maps to precisely identify and explore radioactive materials in densely populated scenarios. Leveraging advanced machine vision technology alongside the capabilities of multi-radiation detectors, this methodology facilitates accurate detection and enables timely responses to potential threats. By aligning image overlay techniques with thorough ray count map analysis, a robust system is established for monitoring and investigating instances of out-of-control radioactive materials. These findings exhibit promising outcomes for enhancing safety protocols in intricate environments, particularly emphasizing the importance of radiation monitoring and the swift identification of out-of-control radioactive materials to safeguard public health and the environment. The rapid expansion of nuclear technology on a global scale has heightened concerns regarding the significant risks posed by radioactive materials to both human societies and the environment. In environments characterized by high levels of traffic and congestion, the effective detection and tracking of out-of-control radioactive materials are paramount to ensuring the safety and security of individuals and communities. This study introduces an innovative and efficient method that integrates machine vision system images with radiation-counting maps to precisely identify and explore radioactive materials in densely populated scenarios. Leveraging advanced machine vision technology alongside the capabilities of multi-radiation detectors, this methodology facilitates accurate detection and enables timely responses to potential threats. By aligning image overlay techniques with thorough ray count map analysis, a robust system is established for monitoring and investigating instances of out-of-control radioactive materials. These findings exhibit promising outcomes for enhancing safety protocols in intricate environments, particularly emphasizing the importance of radiation monitoring and the swift identification of out-of-control radioactive materials to safeguard public health and the environment. https://modelling.semnan.ac.ir/article_9698_30ee210644579125f815990cd95f8cb3.pdf