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All Journal Journal of Computer Engineering, Electronics and Information Technology
Mohammad Rafiqul Farzan
Politeknik Negeri Cilacap
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Other

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Physical Distancing Detection System using OpenCV Based on Raspberry Pi4 Mohammad Rafiqul Farzan
Journal of Computer Engineering, Electronics and Information Technology Vol 1, No 2 (2022): COELITE: Volume 1, Issue 2, 2022
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/coelite.v1i2.59702

Abstract

The Covid-19 pandemic is a disease that is ravaging all over the world, one of which is in our country, namely Indonesia. At this time, officers are still monitoring physical distancing by giving direct warnings to physical distancing violators. Monitoring system that aims to detect physical distancing violations using detection based on biometric identification using faces. The monitoring system uses a Mixio F10 webcam with 1080p resolution which is processed with a Raspberry Pi 4 microcomputer with specifications of 4 GB RAM and an SD Card to store the Raspbian operating system. The distance detection program between faces uses the Python programming language and requires the Open CV library. USB Speaker as an output medium in the form of sound as a warning against physical distancing violators. The tool detects the distance between adjacent faces equipped with a voice indicator if the distance between faces exceeds a predetermined distance with a maximum distance of 3 meters and the level of accuracy of face detection depends on the distance of the face to the camera.
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