Speaker
Description
Environmental radiation monitoring systems are required to provide reliable information on changes in ambient radiation levels and to support the early detection of abnormal radiological events. However, conventional monitoring systems mainly rely on dose-rate measurements, which provide limited information for identifying the origin of radiation level variations. This study presents a conceptual design of an integrated environmental radiation monitoring system combining multiple radiation detectors with artificial intelligence-based data analysis.
The proposed system consists of a high-pressure ionization chamber for ambient gamma dose-rate monitoring, a LaBr₃(Ce) scintillation detector for gamma-ray spectroscopy and radionuclide identification, and a BGO detector for monitoring high-energy radiation components, including cosmic-ray contributions. Radiation measurement data will be analyzed together with environmental and meteorological parameters to distinguish normal background variations from abnormal radiation events. Reference measurements under low-background conditions are also considered for characterizing cosmic-ray contributions and improving the reliability of the analysis. The proposed framework is intended to improve the interpretation of environmental radiation data, support more reliable identification of abnormal events, and reduce false alarms in environmental radiation monitoring.
| Topics | T4. Shielding and dosimetry |
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