COVID-19: Machine learning for safe transportation

Abstract

Entire world has been affected by Covid-19 pandemic. In fighting against the Covid-19, social distancing and face mask have a paramount role in freezing the spread of the disease. People are asked to limit their interactions with each other, to reduce the spread of the disease. Here an alert system has to be maintained to caution people traveling in vehicles. Our proposed solution will work primarily on computer vision. The video stream is captured using a camera. Footage is processed using single shot detector algorithm for face mask detection. Second, YOLOv3 object detection algorithm is used to detect if social distancing is maintained or not inside the vehicle. If passengers do not follow the safety rules such as wearing a mask at any point of the time in the whole journey, alarm/alert is given via buzzer/speaker. This ensures that people abide by the safety rules without affecting their daily norms of transportation. It also helps the government to keep the situation under control.