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

被引：12

作者：

Meivel, S. ^{[1
]}

Sindhwani, Nidhi ^{[2
]}

Anand, Rohit ^{[3
]}

Pandey, Digvijay ^{[4
]}

Alnuaim, Abeer Ali ^{[5
]}

Altheneyan, Alaa S. ^{[5
]}

Jabarulla, Mohamed Yaseen ^{[6
]}

Lelisho, Mesfin Esayas ^{[7
]}

机构：

[1] M Kumarasamy Coll Engn, Karur, Tamil Nadu, India

[2] Amity Univ, AIIT, Noida, India

[3] DSEU, GB Pant Okhla 1 Campus, New Delhi, India

[4] Dr APJ Abdul Kalam Tech Univ Lucknow, Dept Syst Educ, IET Lucknow, Lucknow, India

[5] King Saud Univ, Coll Appl Studies & Community Serv, Dept Comp Sci & Engn, POB 22459, Riyadh 11495, Saudi Arabia

[6] Gwangju Inst Sci Technol, Sch Elect Engn & Comp Sci, Gwangju, South Korea

[7] Mizan Tepi Univ, Dept Stat, Coll Nat & Computat Sci, Tepi, Ethiopia

来源：

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE | 2022年 / 2022卷

关键词：

FACE MASK; FRAMEWORK; COVID-19; IOT;

D O I：

10.1155/2022/2103975

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页数：13

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