Multisensor-Based Multitasking Goggles to Reduce Road Accidents

Due to high workload and pressure, people often find themselves physically and mentally exhausted. Most individuals require adequate and restful sleep to recover from such intense workload. As a consequence, there is a rapid increase in car accidents. While various factors contribute to car accidents, driver drowsiness is the leading cause. Driver drowsiness is a huge problem nowadays, and it is not an unknown fact everyone knows about, but only a few solutions exist. It should be mandatory for every vehicle because it can save people lives. By developing our paper, we are resolving a significant issue that will prevent accidents brought on by drowsy and alcoholic driving. The first objective of the paper is to determine whether the driver is sleepy or not. So, for that, we have devised an idea called the Driver Drowsiness Detection Goggles (DDDG). It can observe drivers eye blink expressions using an IR sensor, and at the same time, it will give an alarm when drivers are sleepy. The second objective is to detect whether the driver has consumed alcohol. After drinking alcohol, if somebody wants to drive a car, that is the most dangerous decision one can take because the increasing rate of a vehicle on the road is massive. For that reason, road accident is increasing acutely. The main objective of our paper is to develop a multitasking model to reduce road accidents based on multisensors.