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Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm.
Meivel, S; Sindhwani, Nidhi; Anand, Rohit; Pandey, Digvijay; Alnuaim, Abeer Ali; Altheneyan, Alaa S; Jabarulla, Mohamed Yaseen; Lelisho, Mesfin Esayas.
  • Meivel S; M. Kumarasamy College of Engineering, Karur, Tamil Nadu, India.
  • Sindhwani N; AIIT, Amity University, Noida, India.
  • Anand R; DSEU, G. B. Pant Okhla-1 Campus, New Delhi, India.
  • Pandey D; Department of Technical Education, IET Lucknow, Dr. A. P. J Abdul Kalam Technical University Lucknow, Lucknow, India.
  • Alnuaim AA; Department of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, P.O. Box 22459, Riyadh 11495, Saudi Arabia.
  • Altheneyan AS; Department of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, P.O. Box 22459, Riyadh 11495, Saudi Arabia.
  • Jabarulla MY; School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Republic of Korea.
  • Lelisho ME; Department of Statistics, College of Natural and Computational Science, Mizan-Tepi University, Tepi, Ethiopia.
Comput Intell Neurosci ; 2022: 2103975, 2022.
Article in English | MEDLINE | ID: covidwho-1759493
ABSTRACT
The drones can be used to detect a group of people who are unmasked and do not maintain social distance. In this paper, a deep learning-enabled drone is designed for mask detection and social distance monitoring. A drone is one of the unmanned systems that can be automated. This system mainly focuses on Industrial Internet of Things (IIoT) monitoring using Raspberry Pi 4. This drone automation system sends alerts to the people via speaker for maintaining the social distance. This system captures images and detects unmasked persons using faster regions with convolutional neural network (faster R-CNN) model. When the system detects unmasked persons, it sends their details to respective authorities and the nearest police station. The built model covers the majority of face detection using different benchmark datasets. OpenCV camera utilizes 24/7 service reports on a daily basis using Raspberry Pi 4 and a faster R-CNN algorithm.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Internet of Things Limits: Humans Language: English Journal: Comput Intell Neurosci Journal subject: Medical Informatics / Neurology Year: 2022 Document Type: Article Affiliation country: 2022

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Internet of Things Limits: Humans Language: English Journal: Comput Intell Neurosci Journal subject: Medical Informatics / Neurology Year: 2022 Document Type: Article Affiliation country: 2022