# IoT and AI-enabled Physical Distance Monitoring Application to Prevent COVID19 Transmission
> Furqan M.D.

URL kanonis: https://discover.unhas.ac.id/publications/iot-and-ai-enabled-physical-distance-monitoring-application-to-prevent-covid19-t
Jurnal / Konferensi: Proceedings 2022 IEEE International Conference on Cybernetics and Computational Intelligence Cyberneticscom 2022
Tahun terbit: 2022
DOI: https://doi.org/10.1109/CyberneticsCom55287.2022.9865290
Citations: 2

## Authors
- Furqan M.D.

## Abstract
During COVID19 pandemic, people are encouraged to practice physical distancing at least 1 meter when interacting with other people to prevent the spread of the COVID19. This study aims to develop a system that can monitor the physical distancing and track physical contact in a room using internet of things (IoT) and artificial intelligent technology. The system consists of a small single-board computer (Raspberry Pi), webcam, and web application displaying physical contact information. The system uses YOLO algorithms to detect the human object and euclidean distance formula to determine the distance between human objects. We evaluated the performance of YOLOv3 and YOLOv3-tiny running on Raspberry Pi. The evaluation result shows that YOLOv3 consumes more CPU resources than YOLOv3-tiny but has better accuracy in detecting human objects. YOLOv3-tiny can process images and detect objects faster than YOLOv3.

## Keywords
- Computer science
- Raspberry pi
- Process (computing)
- Artificial intelligence
- Distancing
- Transmission (telecommunications)
- Internet of Things
- Object (grammar)
- The Internet
- Human–computer interaction
- Computer vision
- Computer security
- Coronavirus disease 2019 (COVID-19)
- World Wide Web
- Operating system
- Telecommunications
- Pathology
- Medicine
- Disease
- Infectious disease (medical specialty)

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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