<![CDATA[This research addresses the problem of undetected falls and hazardous incidents in household bathrooms, especially for children and elderly users who are vulnerable to slipping on wet and narrow surfaces. The study aims to design and implement a smart bathroom security monitoring system using an ESP32 microcontroller, PIR sensor, magnetic sensor, load cell with HX711, and MPU6050 that is connected to the Internet of Things to provide real-time notifications to caregivers via mobile applications. The methodology follows a prototype-based IoT engineering approach, starting from literature review and requirement analysis, followed by hardware–software design, prototyping, iterative testing, and final evaluation in a simulated bathroom environment for various fall scenarios. Experimental data consist of PIR logs, weight changes, system response times, and environmental conditions, which are analyzed statistically to determine accuracy, reliability, and responsiveness of the system. The results show that the prototype is able to detect suspicious motion and fall patterns with good accuracy and trigger local alarms and Telegram notifications within approximately 2–3 seconds, while remaining operable in humid bathroom conditions. It can be concluded that the proposed system meets the research objectives as a low-cost, privacy-preserving bathroom safety solution for smart homes, with future work directed toward integrating machine learning-based fall detection and expanding communication options beyond WiFi to enhance robustness in diverse residential environments]]>
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