Artificial Intelligence-based Dashboard for Radiation Level Monitoring and Analysis Prototype

Keywords:
Radiation Monitoring, Anomaly Detection, Time Series, Machine Learning, Data Visualization.

Abstract:
This paper presents a prototype system for monitoring and analysing radiation levels using machine learning techniques. The system is designed as a web-based application that enables visualization of radiation data and detection of anomalies in time-series data. The proposed solution includes an interactive dashboard, anomaly detection module, and data management functionalities. The main goal of this work is to demonstrate how machine learning and data visualization can be applied to create an early warning system for abnormal radiation levels.

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K. Raković, T. Živković, M. Živković, A. Petrović, “Artificial Intelligence-based Dashboard for Radiation Level Monitoring and Analysis Prototype,” in Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science, Belgrade, Singidunum University, Serbia, 2026, pp. 53-59. doi:10.15308/Sinteza-2026-53-59

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Raković, K., Živković, T., Živković, M., Petrović, A. (2026). Artificial Intelligence-based Dashboard for Radiation Level Monitoring and Analysis Prototype. Paper presented at Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science. doi:10.15308/Sinteza-2026-53-59

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