• International Journal of Technology (IJTech)
  • Vol 13, No 6 (2022)

IoT-Based Indoor and Outdoor Self-Quarantine System for COVID-19 Patients

IoT-Based Indoor and Outdoor Self-Quarantine System for COVID-19 Patients

Title: IoT-Based Indoor and Outdoor Self-Quarantine System for COVID-19 Patients
Chung Gwo Chin, Tong Jia Jian, Lee It Ee, Pang Wai Leong

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Cite this article as:
Chin, C.G., Jian, T.J., Ee, L.I., Leong, P.W., 2022. IoT-Based Indoor and Outdoor Self-Quarantine System for COVID-19 Patients. International Journal of Technology. Volume 13(6), pp. 1231-1240

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Chung Gwo Chin Faculty of Engineering, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor, Malaysia
Tong Jia Jian Faculty of Engineering, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor, Malaysia
Lee It Ee Faculty of Engineering, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor, Malaysia
Pang Wai Leong Faculty of Engineering, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor, Malaysia
Email to Corresponding Author

Abstract
IoT-Based Indoor and Outdoor Self-Quarantine System for COVID-19 Patients

Even after two years since the declaration of the new virus Coronavirus Disease 19 (COVID-19), the reported cases are still considerably high in many countries, including Malaysia. The health authorities cannot monitor the health condition and track the location of every home-monitored patient at once due to many confirmed cases in a day. In order to overcome the shortage of manpower, an Internet of Things (IoT)-based self-quarantine system with Radio Frequency Identification (RFID) and Global Positioning System (GPS) tracking is proposed in this paper to monitor the health conditions of the Covid-19 patients and track their real-time location via mobile application. Biomedical sensors are used to measure health conditions such as temperature, pulse oximetry, and heart-rate monitor. In addition, the RFID readers are used to detect patients that intend to leave the quarantine area, and the GPS modules are used to track their actual geometrical location so that the authorities can take further action. The real-time data is automatically pushed to the cloud server for the authorities to remotely view the patient's health condition and location on the Google map using smart devices. Finally, a hardware prototype and a mobile application have been successfully developed in this project. The system is able to display the temperature, heartbeats, and blood oxygen saturation properly on a liquid crystal display (LCD) screen. All these measured values, together with the information from RFID detection and GPS location tracking, can be viewed on a smartphone.

COVID-19; Global Positioning System; Internet of Things; Radio Frequency Identification; ThingSpeak

Introduction

    In 2020, a new virus was identified: Coronavirus Disease 19 (COVID-19). The World Organization (WHO) has declared COVID-19 as a new pandemic (Dos-Santos, 2020). A retrospective analysis of healthcare workers (HCWs) who had COVID-19 telephonic symptom screening and nasopharyngeal Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) testing was conducted (Lam et al., 2020). In this article, the symptons of COVID-19 are found as fever, cough, shortness of breath, myalgia, sore throat, nasal and gastrointestinal symptoms, etc. Malaysia's Ministry of Health (MOH) has classified five different categories of COVID-19 according to the patients' symptoms (Malaysia's Ministry of Health, 2022). Every adult under the age of 60 with mild Category 1 and Category 2 illnesses, without or with stable or controlled comorbidities only, are eligible for self-quarantine at home or at special isolation units (Yatmo et al., 2021).

    As reported in (Reddy et al., 2021; Sabukunze et al., 2021), biomedical sensors can be used to monitor the health conditions of COVID-19 patients at home. In these two articles, sensors such as infrared temperature and oximeter were used to monitor the patients whether they had fever or shortness of breath. This research has been extended in (Patii et al., 2017; Mazuki et al., 2021) by including a Global Positioning System (GPS) module. The feature of GPS is very useful for tracking the position of patients, but it requires a microcontroller board with a standalone wireless function, such as a NodeMCU wireless module. All these articles implemented the function of the Internet of Things (IoT) (Singh et al., 2020), which shared the results collected from the sensors with the health authorities and the patients to monitor the patients' illness without any human involvement at any level (Kamarozaman & Awang, 2021). Another indoor IoT-based system (Petrovi? et al., 2020) has also been reported to detect mask and social distancing. Besides that, the related work in (Akash et al., 2020) showed the functions of the mobile application, such as displaying the data and notifications, which are useful for the health authorities to monitor the patients' illnesses and receive notifications for abnormal health conditions.

       Although many systems have been developed for COVID-19, none offer a complete solution on how the health authorities can monitor every patient's health conditions in real-time, while ensuring that they do not leave the quarantine area intentionally. This is crucial as patients cannot get treatment early if their illness has developed from mild to severe, and they might spread the virus to others, leading to more citizens being infected by COVID-19. Reports in Indonesia showed catastrophic losses due to this pandemic (Berawi, 2020a), leading to fatalities and bringing instability to many social and economic urban areas globally (Berawi, 2020b). As a result, this project proposed using the IoT platform to create a complete self-quarantine system for COVID-19 patients. It consists of an indoor health monitoring and tracking system using biomedical sensors and RFID, and an outdoor location tracking system using the GPS module. For the indoor system, the patients' readings of the temperature, beats per minute (BPM) and blood oxygen saturation (SpO2) will be pushed to the IoT platform to allow the health authorities to view the real-time data collected. The RFID reader, placed near the door in the patients' house, will also detect the RFID tag kept by the patients if they try to leave the quarantine area without permission. For the outdoor system, health authorities can remotely track the patients' real-time location using the GPS tracker worn by the patients if they are not within their self-quarantine area. Finally, a mobile application will be developed to register the COVID-19 ' information and allow the health authorities to view the health readings collected from the patients and their current geometrical locations and receive important notifications regarding their abnormal health conditions.

Experimental Methods

System Architecture

2.1. System Overview

        In this project, there are two types of proposed systems: indoor and outdoor systems. The indoor system would be used to register and monitor the patients' health conditions and track whether they left the quarantine area indoors. In contrast, the outdoor system is used to track the patients' location if they leave the quarantine area. Figure 1 illustrates the overall system architecture of the proposed system.

For the indoor system, the Arduino Mega is used as a microcontroller to collect the results from the sensors and send them to the IoT server. The MLX90614 non-contact infrared temperature sensor will measure the patients' temperature. The MAX30100 pulse oximeter and heart-rate oximetry sensor module will measure the pulse rate and SpO2 of the patients. The Mifare RC522 RFID reader is used to detect the RFID tag and placed at the room's exit. The liquid crystal display (LCD) will display the results and alert the patients to abnormal health conditions. The ESP8266 ESP-01 Wi-Fi module will connect to the internet and send the data to the IoT server, ThingSpeak, through Hypertext Transfer Protocol (HTTP). A mobile application is developed to display the results sent from the Arduino, send a notification if the patient's health condition is abnormal, and also send an alert when the RFID tag is detected.

For the outdoor system, a GPS tracker is used to track the patients who have left the house. The hardware used to develop the GPS tracker is the NodeMCU Lua V3 ESP8266 ESP-01 Wi-Fi module and the GY-NEO6MV2 flight control GPS module. First, the GPS module will detect the latitude and longitude of the location, and then the NodeMCU will send the result to the cloud-hosted database, Firebase. Finally, the mobile application will display the latitude and longitude of the location obtained from the Firebase on the map.

Figure 1 Block diagram of the proposed system

2.2. Hardware Description

        The schematic diagrams of the indoor and outdoor systems are designed as shown in Figure 2 and Figure 3. The components used are labeled on the schematic diagrams, and their functions are described in Table 1. The novelty of the developed electronic circuits is the measurement accuracy, wearability (outdoor system), and cost of less than $50.

Figure 2 Schematic diagram of the indoor system

Figure 3 Schematic diagram of the outdoor system

Table 1 Functions of the components

Component

Function

Arduino Mega

To control the functions of the components connected to it and process the received results from the modules.

MLX90614 infrared temperature sensor

To measure the temperature of the patients.

MAX30100 pulse oximeter and heart-rate oximetry sensor

To measure the BPM and SpO2 of the patients.

Mifare RC522 RFID

To detect RFID tags, the patients carry to know whether they leave the quarantine unauthorized.

LCD

To display the results obtained from the sensors.

NodeMCU ESP8266

To control the functions of the component connected to it, connect to the internet, and process the received results from the module.

GY-NEO6MV2 flight control GPS

To get the position of the patients in terms of longitude and latitude.

ESP8266 ESP-01 Wi-Fi

To connect to the internet and push the data to the cloud server.

ESP8266 ESP-01 Wi-Fi

To connect to the internet and push the data to the cloud server.

2.3.  Software Description

        The self-quarantine system's proposed algorithm, and flow charts are shown in Figures 4, 5 and 6. The system will first detect any patient leaving the quarantine area by checking the status of the RFID tag, RFID_val, that is installed on each exit. If yes, the system will track each patient's GPS location from Firebase and count the number of a person leaving, counter_RFID. Otherwise, it will check any abnormal temperature, temperature_val, when the patient wants to measure it by pressing a button. It will also check the patient for abnormal SpO2, SpO2_val, and BPM, BPM_val when the patient puts a finger on the oximeter. The status of these readings as well as alerts will then be sent to the user's or authorities' mobile phone through ThinkSpeak for necessary action.

        The detailed process of the indoor system is shown in Figure 6. The Arduino will first connect to the internet through the Wi-Fi module and turn on all the sensors. Then, it will count how many times the RFID module detects the RFID tag. Otherwise, it will check the input signals from the push button and oximetry sensor. If the push button is pressed, the temperature sensor will measure the patient's temperature. For example, if the patient's temperature is higher than 37.5?C, the LCD screen will display "Fever", or else it will display "Normal". On the other hand, if the oximetry sensor detects a finger by reading the IR value, the oximetry sensor will measure the BPM and SpO2 of the patient. For example, if the patient's BPM is higher than 100 or lower than 60, the LCD will display "Abnormal BPM". Then if the patient's SpO2 is lower than 94%, the LCD will display "Low SpO2", else it will display "Normal BPM and Normal SpO2". All these results are then displayed on the LCD screen and also sent to ThingSpeak.

Figure 4 Algorithm of the self-quarantine system       

Figure 5 Outdoor system flow chart