DESIGN AND IMPLEMENTATION OF EDGE COMPUTING SUBSYSTEM FOR EARLY DETECTION SYSTEM OF FEVERISH INFECTIOUS DISEASE IN PUBLIC AREAS

After the global outbreak of the Covid-19 pandemic, human concerns about health and safety have increased. However, there are still individuals who knowingly or unknowingly carry infectious diseases and engage in activities on campus. This poses a risk of disease transmission within the campus area,...

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Main Author: Ignacia Surya, Steven
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/75250
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:75250
spelling id-itb.:752502023-07-26T10:38:44ZDESIGN AND IMPLEMENTATION OF EDGE COMPUTING SUBSYSTEM FOR EARLY DETECTION SYSTEM OF FEVERISH INFECTIOUS DISEASE IN PUBLIC AREAS Ignacia Surya, Steven Indonesia Final Project IoT, Face Recognition, Feverish Infectious Disease, Edge Computing Device, Automatic Detection, Raspberry Pi, VGG16. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/75250 After the global outbreak of the Covid-19 pandemic, human concerns about health and safety have increased. However, there are still individuals who knowingly or unknowingly carry infectious diseases and engage in activities on campus. This poses a risk of disease transmission within the campus area, affecting students, faculty, and staff, and hindering normal activities. Indirectly, those who are exposed or infected incur medical expenses, work or learning absences, and even hospitalization. Due to its limitations and potential inefficiencies, online learning has emerged as a necessary alternative for in-class instruction. Therefore, it is important to develop and implement strategies to address the spread of infectious diseases within the campus environment and ensure the continuity of educational and professional activities. Consequently, a screening system is required to enable early detection of infectious diseases, particularly those related to fever, in order to limit the spread of infectious diseases in public environments. Based on the above description, a solution is proposed in the form of an IoT system called "Early Detection System for Infectious Diseases in Public Areas". One component of this system is the utilization of edge computing. The task of edge computing is to perform suspect identification based on facial image and temperature data captured from sensors through MQTT Protocol. Once a suspect is detected, the data will be sent to the cloud through HTTPS protocol, and the user will receive a warning notification via WhatsApp if their temperature exceeds the normal limit. In this system, edge computing is implemented using Raspberry Pi 4B as the hardware. Edge computing performs face recognition using a CNN algorithm with the VGG16 architecture. Generally, functional testing for each function has been successfully conducted. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description After the global outbreak of the Covid-19 pandemic, human concerns about health and safety have increased. However, there are still individuals who knowingly or unknowingly carry infectious diseases and engage in activities on campus. This poses a risk of disease transmission within the campus area, affecting students, faculty, and staff, and hindering normal activities. Indirectly, those who are exposed or infected incur medical expenses, work or learning absences, and even hospitalization. Due to its limitations and potential inefficiencies, online learning has emerged as a necessary alternative for in-class instruction. Therefore, it is important to develop and implement strategies to address the spread of infectious diseases within the campus environment and ensure the continuity of educational and professional activities. Consequently, a screening system is required to enable early detection of infectious diseases, particularly those related to fever, in order to limit the spread of infectious diseases in public environments. Based on the above description, a solution is proposed in the form of an IoT system called "Early Detection System for Infectious Diseases in Public Areas". One component of this system is the utilization of edge computing. The task of edge computing is to perform suspect identification based on facial image and temperature data captured from sensors through MQTT Protocol. Once a suspect is detected, the data will be sent to the cloud through HTTPS protocol, and the user will receive a warning notification via WhatsApp if their temperature exceeds the normal limit. In this system, edge computing is implemented using Raspberry Pi 4B as the hardware. Edge computing performs face recognition using a CNN algorithm with the VGG16 architecture. Generally, functional testing for each function has been successfully conducted.
format Final Project
author Ignacia Surya, Steven
spellingShingle Ignacia Surya, Steven
DESIGN AND IMPLEMENTATION OF EDGE COMPUTING SUBSYSTEM FOR EARLY DETECTION SYSTEM OF FEVERISH INFECTIOUS DISEASE IN PUBLIC AREAS
author_facet Ignacia Surya, Steven
author_sort Ignacia Surya, Steven
title DESIGN AND IMPLEMENTATION OF EDGE COMPUTING SUBSYSTEM FOR EARLY DETECTION SYSTEM OF FEVERISH INFECTIOUS DISEASE IN PUBLIC AREAS
title_short DESIGN AND IMPLEMENTATION OF EDGE COMPUTING SUBSYSTEM FOR EARLY DETECTION SYSTEM OF FEVERISH INFECTIOUS DISEASE IN PUBLIC AREAS
title_full DESIGN AND IMPLEMENTATION OF EDGE COMPUTING SUBSYSTEM FOR EARLY DETECTION SYSTEM OF FEVERISH INFECTIOUS DISEASE IN PUBLIC AREAS
title_fullStr DESIGN AND IMPLEMENTATION OF EDGE COMPUTING SUBSYSTEM FOR EARLY DETECTION SYSTEM OF FEVERISH INFECTIOUS DISEASE IN PUBLIC AREAS
title_full_unstemmed DESIGN AND IMPLEMENTATION OF EDGE COMPUTING SUBSYSTEM FOR EARLY DETECTION SYSTEM OF FEVERISH INFECTIOUS DISEASE IN PUBLIC AREAS
title_sort design and implementation of edge computing subsystem for early detection system of feverish infectious disease in public areas
url https://digilib.itb.ac.id/gdl/view/75250
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