DriveGuard: An Automated Interactive Alerting System to track and Analyze Drivers’ Behaviors on Road

The increasing number of road accidents globally has highlighted the need for advanced safety measures in vehicular transportation. Driver alerting systems have emerged as a critical solution to reduce the risks associated with human error, fatigue, and distraction. These systems employ a combination of computer vision techniques, and machine learning algorithms to monitor driver behavior and vehicle performance in real-time. Driver alerting systems can mitigate hazardous situations such as sudden lane departures, inadequate mirror checks, and drowsy driving by providing timely alerts and interventions.This paper discusses the importance of driver alerting systems in enhancing road safety, improving driver performance, and reducing accident rates. It delves into the various technologies and methodologies utilized in the development of these systems, along with their potential integration with emerging connected and autonomous vehicle technologies. Throughout this paper, it is shown how using the application helped 75% of people have more focus while driving, this conclusion came from a conducted survey on people before and after using the application. The system also scored 81 point on average for the System Usability Scale (SUS) usability test. Ultimately, the widespread adoption of driver alerting systems is paramount to creating a safer and more sustainable transportation ecosystem.