<![CDATA[atigue and drowsiness are major causes of accidents, particularly in activities that require high levels of concentration, such as driving. To address this issue, this research focuses on designing an early warning system capable of effectively detecting signs of drowsiness and fatigue using Internet of Things (IoT) technology. The research method employed is system engineering, which includes needs identification, hardware and software design, implementation, and system testing and evaluation. The proposed solution is an IoT-based automatic monitoring system that integrates a Raspberry Pi camera for drowsiness detection, a smartwatch for monitoring fatigue through heart rate tracking, and an ESP32 microcontroller as the central control unit. The system provides three levels of response based on the user's condition: normal (Telegram notification), slightly drowsy or fatigued (Telegram notification, buzzer beeps twice, and mild audio alert), and severely drowsy or fatigued (Telegram notification, buzzer beeps five times, and main audio alert). The system implementation includes the MP3-TF-16P module, passive speaker, and Telegram bot for alert delivery. Trial results indicate that the system is capable of responding to user conditions in real time and delivering effective warnings, thereby potentially reducing the risk of accidents caused by fatigue and drowsiness.]]>
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