An IoT-powered smart helmet to avoid drowsiness and theft protection
DOI:
https://doi.org/10.61179/infact.v9i02.737Keywords:
Helmet, ESP32-C3, IoT, Blynk, WhatsAppAbstract
Helmets are mandatory equipment for motorcyclists, but current helmets only serve to reduce injuries during accidents. Accidents often occur due to human error, such as drowsiness while riding which endangers the rider and others. In addition, helmets are also vulnerable to theft if they are far from the owner. This research aims to reduce these problems by adding drowsiness warning and theft detection features to the helmet. The drowsiness warning feature uses MAX30102 sensor to detect heart rate as a parameter of drowsiness condition, while the theft detection feature uses magnetic reed switch sensor as a switch with magnet as a parameter of theft. Through IoT technology, riders can monitor their heart rate in real-time and receive notifications in case of theft. Tests show that the drowsiness warning feature has an error rate of 3.23% in detecting microsleep and the theft detection feature is able to send warning messages with an average time of 8 seconds.
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