<![CDATA[Monitoring radon gas concentrations in various environments, such as residential areas, buildings, caves, and mining sites, is crucial to minimizing health risks associated with radon exposure exceeding the 100 Bq/m³ threshold set by the World Health Organization (WHO). Additionally, anomalies in radon concentration in fault zones are often considered precursors to seismic activity. Therefore, this study develops a real-time Internet of Things (IoT)-based radon gas monitoring system using a cost-effective approach. The system utilizes a ZnS(Ag)-based scintillation detector combined with a Photo Multiplier Tube (PMT) model H10492-001 (Hamamatsu, Japan). Calibration results at the Geological Resource Research Center – BRIN Bandung indicate that the detector has an average efficiency of 79.8%. The cloud-based monitoring system is developed using PHP 8.0 and MySQL 10.5, with performance evaluation conducted through an API using the GET method via the cURL application. Testing with various intervals and iterations shows that the system achieves 99% data reception and recording efficiency compared to the data sent by the test device. Performance testing using Chrome DevTools indicates a response time ranging from 32–140 ms, demonstrating that the system responds quickly and efficiently handles user requests. The system includes an early warning mechanism that activates when sensor data exceeds a predefined threshold, featuring a red indicator on the dashboard, an alarm sound, and automatic notifications to a Telegram bot. Responsiveness testing confirms that the dashboard display adapts optimally to various screen sizes, ensuring accessibility across multiple devices. From a cybersecurity perspective, the system implements HTTPS protocols and has received an A rating from www.ssllabs.com. It also employs BCrypt encryption with a 184-bit hash length for password protection.]]>
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