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. 2022 Feb 1:2022:2103975.
doi: 10.1155/2022/2103975. eCollection 2022.

Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm

S Meivel  1 , Nidhi Sindhwani  2 , Rohit Anand  3 , Digvijay Pandey  4 , Abeer Ali Alnuaim  5 , Alaa S Altheneyan  5 , Mohamed Yaseen Jabarulla  6 , Mesfin Esayas Lelisho  7
Affiliations

Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm

S Meivel et al. Comput Intell Neurosci. .

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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Conflict of interest statement

The authors declare that there are no conflicts of interest.

Figures

Figure 1
Figure 1
Constituents of the proposed model.
Figure 2
Figure 2
Convolution theorem.
Figure 3
Figure 3
Flow process of the proposed methodology.
Figure 4
Figure 4
Pseudocode for detection of bounding box using OpenCV camera.
Figure 5
Figure 5
Count of the testing dataset in various classnames.
Figure 6
Figure 6
Variation of validation loss with training models.
Figure 7
Figure 7
Variation of validation accuracy with training models.
Figure 8
Figure 8
Mask count (pink colored) and unmask count (green colored).
Figure 9
Figure 9
Social distance maintenance and green/orange/red object detection.
Figure 10
Figure 10
Overview of the drone monitoring system components.
See this image and copyright information in PMC

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