Home > Computer Science > Other > Volume-9 > Issue-2 > Deep Learning-Based Face Mask Recognition: A Smart Solution for Health Compliance

Deep Learning-Based Face Mask Recognition: A Smart Solution for Health Compliance

Call for Papers

Volume-9 | Issue-4

Last date : 27-Aug-2025

Best International Journal
Open Access | Peer Reviewed | Best International Journal | Indexing & IF | 24*7 Support | Dedicated Qualified Team | Rapid Publication Process | International Editor, Reviewer Board | Attractive User Interface with Easy Navigation

Journal Type : Open Access

First Update : Within 7 Days after submittion

Submit Paper Online

For Author

Research Area


Deep Learning-Based Face Mask Recognition: A Smart Solution for Health Compliance


Mansi Puri | Manisha Kadam



Mansi Puri | Manisha Kadam "Deep Learning-Based Face Mask Recognition: A Smart Solution for Health Compliance" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-9 | Issue-2, April 2025, pp.473-479, URL: https://www.ijtsrd.com/papers/ijtsrd78359.pdf

The enforcement of protective measures, such as wearing face masks, has become essential in mitigating the spread of airborne diseases. Traditional methods of monitoring compliance can be labor-intensive and inefficient, leading to the need for automated solutions. Artificial intelligence (AI) and machine learning (ML) have emerged as effective tools for real-time face mask detection, improving efficiency and accuracy in public safety enforcement. This study presents the development and deployment of an intelligent system that utilizes deep learning techniques for mask detection in various environmental conditions. The proposed model is trained on diverse datasets, ensuring robustness against variations in lighting, occlusion, and mask types. By integrating convolutional neural networks (CNNs) and computer vision, the system accurately classifies individuals as masked or unmasked in real-time video streams. The research discusses model architecture, data pre-processing, and implementation strategies while addressing key challenges such as false detections and performance optimization. The findings demonstrate the potential of AI-driven surveillance systems in promoting adherence to health regulations, reducing manual monitoring efforts, and enhancing public safety. Future advancements may focus on improving accuracy, optimizing computational efficiency, and integrating additional features such as thermal screening and voice alerts for broader applications.

Deep Learning, AI-Based Surveillance, Face Mask Compliance, Computer Vision, Public Health Monitoring, Real-Time Detection


IJTSRD78359
Volume-9 | Issue-2, April 2025
473-479
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

Thomson Reuters
Google Scholer
Academia.edu

ResearchBib
Scribd.com
archive

PdfSR
issuu
Slideshare

WorldJournalAlerts
Twitter
Linkedin