Citation

Joseph, Ting Heng Hao and Pang, Wai Leong and Chan, Kah Yoong (2022) Smart Health Monitoring System for Covid-19. Periodic Research Publication, Faculty of Engineering. (Unpublished)

Text 10_1161104011 Joseph Ting_WLPang_FYP2 Poster.pdf Restricted to Repository staff only Download (1MB)

Abstract

Ever since the outbreak of the Covid 19 pandemic, the infection rate has been skyrocketing without signs of stopping all across the globe. Many cases are found within clusters at locations such as education institutes, workplaces and factories where proper ‘Standard of Procedures’ are difficult to enforce. This project aims to create a system that can monitor the individuals within these particular clusters and provide data logging for their symptoms. The proposed system provides proper monitoring on several characteristics closely tied to the Covid 19 symptoms. In addition, multiple functionalities are implemented such as IoT, an email notification system, uploading logged to cloud and most importantly machine learning to provide individuals the ability to determine whether they have contracted the Covid 19 virus. Analysis between 4 different machine learning algorithms are carried out to determine the best algorithm to fit the Covid 19 symptom dataset.

Item Type:	Other
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Assoc. Dr Chee Pun Ooi
Date Deposited:	29 Nov 2022 00:57
Last Modified:	29 Nov 2022 00:57
URII:	http://shdl.mmu.edu.my/id/eprint/10640

Downloads

Edit (login required)