Cargando…
Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm
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 focuse...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8804552/ https://www.ncbi.nlm.nih.gov/pubmed/35116063 http://dx.doi.org/10.1155/2022/2103975 |
_version_ | 1784643096513871872 |
---|---|
author | Meivel, S. Sindhwani, Nidhi Anand, Rohit Pandey, Digvijay Alnuaim, Abeer Ali Altheneyan, Alaa S. Jabarulla, Mohamed Yaseen Lelisho, Mesfin Esayas |
author_facet | Meivel, S. Sindhwani, Nidhi Anand, Rohit Pandey, Digvijay Alnuaim, Abeer Ali Altheneyan, Alaa S. Jabarulla, Mohamed Yaseen Lelisho, Mesfin Esayas |
author_sort | Meivel, S. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8804552 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-88045522022-02-02 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 Comput Intell Neurosci Research Article 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. Hindawi 2022-02-01 /pmc/articles/PMC8804552/ /pubmed/35116063 http://dx.doi.org/10.1155/2022/2103975 Text en Copyright © 2022 S. Meivel et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Meivel, S. Sindhwani, Nidhi Anand, Rohit Pandey, Digvijay Alnuaim, Abeer Ali Altheneyan, Alaa S. Jabarulla, Mohamed Yaseen Lelisho, Mesfin Esayas Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm |
title | Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm |
title_full | Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm |
title_fullStr | Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm |
title_full_unstemmed | Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm |
title_short | Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm |
title_sort | mask detection and social distance identification using internet of things and faster r-cnn algorithm |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8804552/ https://www.ncbi.nlm.nih.gov/pubmed/35116063 http://dx.doi.org/10.1155/2022/2103975 |
work_keys_str_mv | AT meivels maskdetectionandsocialdistanceidentificationusinginternetofthingsandfasterrcnnalgorithm AT sindhwaninidhi maskdetectionandsocialdistanceidentificationusinginternetofthingsandfasterrcnnalgorithm AT anandrohit maskdetectionandsocialdistanceidentificationusinginternetofthingsandfasterrcnnalgorithm AT pandeydigvijay maskdetectionandsocialdistanceidentificationusinginternetofthingsandfasterrcnnalgorithm AT alnuaimabeerali maskdetectionandsocialdistanceidentificationusinginternetofthingsandfasterrcnnalgorithm AT altheneyanalaas maskdetectionandsocialdistanceidentificationusinginternetofthingsandfasterrcnnalgorithm AT jabarullamohamedyaseen maskdetectionandsocialdistanceidentificationusinginternetofthingsandfasterrcnnalgorithm AT lelishomesfinesayas maskdetectionandsocialdistanceidentificationusinginternetofthingsandfasterrcnnalgorithm |