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Face Mask and Social Distancing Detection in Real Time
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Author(s): Madhumita Choudhury (St. Xavier's College, Kolkata, India), Durba Paul (St. Xavier's College, Kolkata, India), Anal Acharya (St. Xavier's College, Kolkata, India), Nisha Banerjee (St. Xavier's College, Kolkata, India)and Debabrata Datta (St. Xavier's College, Kolkata, India)
Copyright: 2023
Pages: 24
Source title:
Perspectives on Social Welfare Applications’ Optimization and Enhanced Computer Applications
Source Author(s)/Editor(s): Ponnusamy Sivaram (G.H. Raisoni College of Engineering, Nagpur, India), S. Senthilkumar (University College of Engineering, BIT Campus, Anna University, Tiruchirappalli, India), Lipika Gupta (Department of Electronics and Communication Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, India)and Nelligere S. Lokesh (Department of CSE-AIML, AMC Engineering College, Bengaluru, India)
DOI: 10.4018/978-1-6684-8306-0.ch011
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Abstract
With the recent outbreak and rapid transmission of the COVID-19 pandemic, the need for the people to follow social distancing and wear masks in public is only increasing. So, the main objective of this chapter is to build a machine learning model based on TensorFlow object detection API and YOLO Objection Detection that will determine a green and red rectangle around the face if the person detected in the camera wears or does not wear a mask, along with an email alert being sent to the authority in charge informing about a person's violation of face mask policy and will return a green or red bounding box accordingly if social distancing is maintained between two people and at the same time alert others by a beep alarm. The accuracy of the model is nearly 97% so it can be used by governments to alert people if the situation turns serious.
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