Implementing Social Distancing Monitoring in Jetson Nano using Convolutional Neural Networks

Working Model Video

Social Distancing Project.pdf (1.1 MB)

Implementation: In this work, a deep learning-based social distance
monitoring framework is presented using an overhead perspective. The pre-trained YOLOv3 paradigm is used for human detection. As a person’s appearance, visibility, scale, size, shape, and pose vary significantly from an overhead view, the transfer learning method is adopted to improve the pre-trained model’s performance. The model is trained on an overhead data set, and the newly trained layer is appended with the existing model.

Authenticated user can login with their username and password and can view
the camera with respective ip address. If the social distance is violated, a
violation alert message will be sent to the admin’s What’sapp number or mail id.

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