<![CDATA[The creation of an Internet of Things-based motor vehicle early prevetion tool (Sitinjau Lauik Case Study) has been completed.. The aim of this research is to develop a tool to minimize accidents caused by human physiological factors such as fatigue and drowsiness. This device utilizes the MPU 6050 sensor, pulse heart sensor, buzzer, vibration motor, GPS, Arduino Uno and Wemos D1 Mini. The research method began with the construction of the device and the permance testing of the system. The results indicate that the system of this device can detect drowsiness or fatigue by measuring the heart rate at less than 70 bpm using the pulse heart sensor and detecting head movements using the MPU 6050 sensor, where the X- axis angle is > 29,23 ° < - 30,63 ° and the Y-axis angle is > 29,33° < -20,12°. When drowsiness is detected, the device sends notifications via the Telegram application containing the driver’s condition, heart rate, andlocation through a Google Maps link. Subsequently, when the driver is drowsy, the buzzer sounds to provide a warning and the vibration motor provides vibration to give a sensory wake-up signal to the driver, helping to awaken them from a drowsy state. Overall, the device functions effectively.]]>
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