Muhamad Aiman, Suhaizi (2022) Analysis on custom dataset of smart crowd Covid monitoring system using NVIDIA Jetson Nano and Yolov5. Faculty of Electrical and Electronic Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah.
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MUHAMAD AIMAN BIN SUHAIZI.pdf - Accepted Version Download (6MB) | Preview |
Abstract
COVID-19 have killed a total of 5 million people around the world since the pandemic started and the numbers are still counting until today. Lots of efforts have been done to fight the pandemic and the most effective effort medically is the COVID-19 vaccine. This project that has been done is one of the many efforts to also fight the virus. Although this effort does not involve anything medical, it may be relevant since the system can help to ensure the people to wear a face mask when going to public places. Wearing a face mask is another good effort to fight the spread or transmission of the virus as the virus spreads through the air when people inhale contaminated air by small airborne particles and droplets. The system's ability to detect the usage of a face mask on a person can produce an environment where everyone wears a face mask properly. The output can also be easily accessed by the authorities so people who disobeys the SOP can be taken action immediately. It is common to punish law breakers and it will also be fine to do so to people who does not wear face mask as it is a new law since the pandemic. This paper also explains in detail on how to create a custom dataset for the system as an analysis on different types of custom datasets have been done to obtain the best result of face mask detection using Deep Leaming method.
| Item Type: | Undergraduates Project Papers |
|---|---|
| Additional Information: | Project Paper (Bachelor of Engineering Technology (Hons.) (Electrical)) -- Universiti Malaysia Pahang – 2022, SV: Mr. Amran bin Abdul Hadi |
| Uncontrolled Keywords: | Covid-19 |
| Subjects: | T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Faculty of Electrical and Electronic Engineering Technology |
| Depositing User: | Mr. Nik Ahmad Nasyrun Nik Abd Malik |
| Date Deposited: | 04 Sep 2024 01:21 |
| Last Modified: | 04 Sep 2024 01:21 |
| URI: | http://umpir.ump.edu.my/id/eprint/42496 |
| Download Statistic: | View Download Statistics |
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