Monitoring environmental radiation around nuclear facilities is critical for safety and regulatory compliance. Traditional methods, such as environmental radiation monitoring using high-pressure ion chambers and thermoluminescent dosimeters, have limitations with regard to cost, complexity, and response time. To address these issues, we developed a compact Geiger-M��ller (GM) counter-based detector network for real-time radiation monitoring at the Korea Atomic Energy Research Institute (KAERI). The developed GM detector module is operated using a battery and a solar panel to ensure maintenance-free operation and is equipped with LTE wireless communication. The Daejeon KAERI site spans approximately 1.42 km, where a total of 50 GM modules were installed, forming a high-resolution radiation monitoring network. In addition, convolutional neural network-based radiation anomaly detection and source-tracking models were developed to enhance the monitoring capabilities. The anomaly-detection model achieved an accuracy of 0.9999 and an area under the receiver operating characteristic curve of 0.9999, effectively distinguishing between normal and anomalous radiation. The source-tracking model predicted source locations with an average error of 3.44 m for the test set. In field experiments using a low-intensity Cs source, the average error was 54.73 m. The proposed cost-effective, high-resolution radiation mapping solution can be easily deployed and maintained, ensuring comprehensive coverage and timely detection of radiation anomalies.
