• P. Swathi
• L. Sasi Sudarsan Reddy
• P. Srinivasulu
• G. Meghana
• U. pallavi

The World Health Organization (WHO) has stated that the spread of the coronavirus (COVID-19) is on a global scale and that wearing a face mask at work is the only effective way to avoid becoming infected with the virus. The pandemic made governments worldwide stay under lock-downs to prevent virus transmissions. Reports show that wearing face masks would reduce the risk of transmission. With the rise in population in cities, there is a greater need for efficient city management in today’s world for reducing the impact of COVID-19 disease. For smart cities to prosper, significant improvements to occur in public transportation, roads, businesses, houses, city streets, and other facets of city life will have to be developed. The autonomous mask detection and alert system are needed to find whether the person is wearing a face mask or not.The main objective of the paper is to detect the presence of face masks in real-time video stream by utilizing deep learning, machine learning, and image processing techniques. To achieve this objective, a hybrid deep and machine learning model was designed and implemented.

COVID-19; artificial intelligence; face mask system; deep learning; smart bus.

"Real-Time Face Mask Detection In Overcrowded Environments Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 4, page no.l309-l314, April-2025, Available :http://www.jetir.org/papers/JETIR2504B35.pdf

"Real-Time Face Mask Detection In Overcrowded Environments Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 4, page no. ppl309-l314, April-2025, Available at : http://www.jetir.org/papers/JETIR2504B35.pdf