Deep Learning and Computer Vision Approaches for Vehicular Safety Systems

While numerous technological solutions have been utilized to locate accidents, few have been utilized to prevent them. There has been an unstoppable increase in the rate of accidents, violations of transit regulations, and criminals finding ways to avoid the legitimate consequences of transcendently quick in-and-out cases. The framework would act as a model for a practical arrangement that focuses on identifying conduct that prevents mishaps. In the event of an accident, it ensures that the victim receives the appropriate compensation. The two modules of the project are prevention and recovery. The prevention module uses Deep Learning and Computer Vision to determine whether the driver is drowsy and uses CNN to send an alert. The recovery module focuses on locating incidents and gathering information about the parties involved in similar incidents. Since they have resulted in significant injuries and fatalities across a wide range, mishaps have been a source of constant worry. There must be a way to cut down on the number of accidents and deaths caused by this.