Application Development for Mask Detection and Social Distancing Violation Detection using Convolutional Neural Networks

Gokul Kumar, Sujala Shetty

Abstract

This project aims to detect face masks and social distancing on a video feed using Machine Learning and Object Detection. TensorFlow and Keras were used to build a CNN model to detect face masks and it was trained on a dataset of 3800 images. YOLO Object detection was used to detect people in a frame and check for social distancing by calculating the Euclidean distance between the centroids of the detected boxes. Developed an Android app named “StaySafe” where the user will be notified and can monitor the violations. For this purpose, Firebase was used as the backend service. If a violation is detected it will upload the image to a Firebase Cloud Storage with a notification, and the user will be able to view these images on their Android app along with the date and time. Firebase Cloud Messaging service was used to send notifications which will be handled in the android app. The app offers various features like viewing history, saving the image to the device, deleting the images from the cloud etc. A heat map can also be viewed which highlights crowded regions which can help officials identify the regions that need to be sanitized more often.

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Paper Citation


in Harvard Style

Kumar G. and Shetty S. (2021). Application Development for Mask Detection and Social Distancing Violation Detection using Convolutional Neural Networks. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-509-8, pages 760-767. DOI: 10.5220/0010483107600767


in Bibtex Style

@conference{iceis21,
author={Gokul Kumar and Sujala Shetty},
title={Application Development for Mask Detection and Social Distancing Violation Detection using Convolutional Neural Networks},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2021},
pages={760-767},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010483107600767},
isbn={978-989-758-509-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Application Development for Mask Detection and Social Distancing Violation Detection using Convolutional Neural Networks
SN - 978-989-758-509-8
AU - Kumar G.
AU - Shetty S.
PY - 2021
SP - 760
EP - 767
DO - 10.5220/0010483107600767