T Traffic accidents in Indonesia remain relatively high, with the causative factors being influenced by a variety of elements, one of which is drowsiness. Drowsiness has the potential to diminish an individual\\\'s level of focus while operating a vehicle. In order to address this issue, a prototype for drowsiness detection has been developed to offer timely alerts to drivers if signs of drowsiness are detected. This system has been enhanced by the integration of a global positioning system (GPS) and will transmit notifications through Blynk. Drowsiness can be identified based on the duration of eye blinks, where an individual is classified as drowsy if the duration of their eye blink exceeds 400 ms. Therefore, the utilization of a proximity sensor FC-51 in the capacity of a drowsiness detection mechanism necessitates a configuration that enables the differentiation between individuals exhibiting drowsy versus alert states. An individual shall be classified as alert if the duration of their eye blink is below 400 milliseconds, while a drowsy designation is assigned to those with eye blink durations exceeding 400 milliseconds. The efficacy in blink detection stands at 94.25%, with an accuracy rate of 95.76% in identifying the distinct states of detection. Subsequently, the rate of auditory alerts activation and the efficacy of the GPS system in pinpointing an individual\\\'s location when drowsiness is detected stands at 97.73%.