Drunken driving detection using IoT

The Internet of Things (IoT) refers to a network of interconnected devices equipped with sensors and communication capabilities. This paper proposes an IoT-based model aimed at enhancing road safety by detecting drunk or drowsy drivers, especially during nighttime hours. The model incorporates analysis of alcohol concentration levels, eye-blinking rates, and pulse rate to identify potentially impaired drivers. Upon detection, countermeasures such as reducing vehicle speed, triggering alarms, notifying traffic authorities, or engaging autopilot functions could be initiated to mitigate risks and prevent accidents. The paper examines existing models and aims to synthesize effective ideas while addressing implementation challenges.