Published Paper Details:

The main objective of this proposed idea is to provide better control over pandemic by monitoring the social distancing among people when used in certain places via video feed . This system will also be able to detect whether people are wearing a face mask .In 2019 one of the most dangerous pandemic in mankind history the coronavirus disease (COVID-19) has brought global crisis with its global spread of virus to more than 180 countries if no less, and about 3,518,901 confirmed cases along with 247,641 deaths globally as on May 10, 2020. The absence of any active Vaccines and the lack of immunity against COVID19 has made the entire human race/population vulnerable . Since there are no vaccines available yet, Governments from all over world has put certain rules like social distancing and wearing a face mask to fight against this pandemic and to control its spread. Motivated by this notion, this article proposes a deep learning based framework for automating the task of monitoring social distancing using video. This proposed framework utilizes the YOLO v3 object detection pre trained model to detect humans from the background and then track those identified people with the help of bounding boxes and then calculate distance to detect social distancing and it also uses keras/tensorflow Mobilenet SSD model to detect face mask from the objects faces.