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<p>Orphan radioactive sources pose a significant environmental and human health threat. This study presents a novel, scalable detection system for localizing and identifying these sources within large areas. Our system integrates a network of radiation detectors with surveillance cameras, employing data fusion algorithms to analyze both radiological and visual data. This multi-sensor approach enables accurate estimation of radionuclide types and the assessment of associated radiological risks. Real-world experiments demonstrate the system’s effectiveness in enhancing the efficiency and accuracy of orphan radioactive source detection, contributing to improved environmental monitoring and the mitigation of potential radiological contamination risks.</p>

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Mitigating environmental risks from orphan radioactive sources in large areas: a multi-sensor fusion approach for enhanced localization and identification

  • 期刊论文

  • 发表日期：

    2025年11月1日

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  • Hadi Ardiny,
  • AmirMohammad Beigzadeh

摘要

Orphan radioactive sources pose a significant environmental and human health threat. This study presents a novel, scalable detection system for localizing and identifying these sources within large areas. Our system integrates a network of radiation detectors with surveillance cameras, employing data fusion algorithms to analyze both radiological and visual data. This multi-sensor approach enables accurate estimation of radionuclide types and the assessment of associated radiological risks. Real-world experiments demonstrate the system’s effectiveness in enhancing the efficiency and accuracy of orphan radioactive source detection, contributing to improved environmental monitoring and the mitigation of potential radiological contamination risks.