Driver’s Drowsiness Detection Using SpO2

Abstract

The driver’s drowsiness detection system is the research conducted in the field of computer engineering to develop a system to prevent accidents caused by driver drowsiness. Due to the rise in traffic accidents, we now suffer a variety of losses that have an impact on both the economy of our country and the next generation of our nation. The rapid increase in the number of vehicles and their speed on the road has worsened traffic congestion and the likelihood of increased traffic accidents. In the upcoming years, it will be crucial to implement a smart accident prevention system because the number of fatalities is rising significantly. Drowsiness can occur in many ways, such as the feeling of being sleepy or a strong desire to sleep for an extended period. Therefore, it is crucial to assess the psychological and biological factors that may influence a driver’s reflexes and shorten reaction time. One of the biggest causes of vehicle accidents is fatigued or exhausted drivers. While operating a vehicle, such as an automobile, one must be concentrated, aware, and cautious. This study presents a method that combines the Internet of Things (IoT) and a physiological approach to assessing blood oxygen levels to identify drivers who are drowsy while operating an automobile. Our technique, which detects tiredness in the driver’s blood in real-time by measuring blood oxygen levels, is effective. Drowsy driving has been criticized for a significant number of traffic accidents in recent years. As a result, we came up with the idea of detecting drowsiness while driving using a pulse oximetry sensor (SpO2). Next, the level of blood oxygen in the driver’s blood is calculated to determine and evaluate the driver’s level of drowsiness. Even though there are numerous other sensors, the goal of utilizing SpO2 is due to the accuracy of the results obtained. The result can be achieved by observing the change in oxygen levels caused by drowsiness. We utilize the SpO2 sensor in our research and projects since the oxygen level predicts the outcome. The alarm system that comes with drowsiness detection will alert the driver due to their lack of concentration and drowsiness. To avoid an accident, the alarm notifies the motorist that they are now exhausted and suggests having a break. Currently, road networks are a major part of human life, so they must be fixed. This research paper is very cost-efficient, and the outcomes obtained are accurate by using the SpO2 sensor for detecting the driver’s drowsiness and the alarm helps the driver in regaining consciousness. Thus, there will be a decline in the rate of road accidents compared to the past. This system additionally uses Arduino UNO & MAX 30100 pulse oximetry sensor as the processing unit and has an LCD for displaying the status.