COVID-19 fever symptom detection based on IoT cloud

Hasan, Mustafa Wassef

doi:10.11591/ijece.v11i2.pp1823-1829

Cited by 25 publications

(14 citation statements)

References 11 publications

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“…The sensors read heartbeat, cough, body temperature and oxygen saturation. This is similar with solution proposed by Hasan [15], which also detect the presence of the disease by using temperature sensor.…”

Section: Related Worksupporting

confidence: 79%

IoT-based COVID-19 Patient Vital Sign Monitoring

Qomariyah

Astriani

Asri³

2021

2021 IEEE 5th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

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The number of COVID-19 cases is growing rapidly, while there is not enough healthcare workers which can help the patients. Even worse, the highly contagious nature of this disease, requires the medical staff to be more restrictive and wear the Personal Protective Equipment (PPE) all the time when handling the patients directly. In this situation, a remote system which can monitor patient progress from a distant is inevitable. The emerge of Internet of Thing (IoT) technology has been implemented in many domain. The availability of smart technology, where almost all devices around us has connectivity to the internet, allow people to automate process from distance. The implementation of IoT has also been shown very helpful in medical domain, especially during the pandemics. The IoT technology can be a suitable solution for monitoring patients with a highly contagious disease. The technology can also be very helpful for people who live far from healthcare facility. This can allow people to report immediately and even connect to the hospital system in real-time. In this paper, we propose the use of three different sensors, namely: heart-rate and pulse oximeter sensor (MAX30102), temperature sensor(DS18b20) and accelerometer sensor, which is integrated in a web-based early warning monitoring system for COVID-19 patients.

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Section: Related Worksupporting

confidence: 79%

IoT-based COVID-19 Patient Vital Sign Monitoring

Qomariyah

Astriani

Asri³

2021

2021 IEEE 5th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

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“…Fever, fatigue, a dry cough, difficulty breathing, sore throat, nasal congestion, runny nose, and diarrhoea are just a few of the pre-defined typical symptoms. These symptoms are based on world health organization (WHO) regulations [3], [12], [13], [19], [20], [25]. The severity of the sickness assists the medical team in isolating patients and providing appropriate health care.…”

Section: Introductionmentioning

confidence: 99%

Comparison of meta-heuristic algorithms for fuzzy modelling of COVID-19 illness’ severity classification

Aseri

Ismail

Fakharudin

et al. 2022

IJ-AI

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The world health organization (WHO) proclaimed the COVID-19, commonly known as the coronavirus disease 2019, was a pandemic in March 2020. When people are in close proximity to one another, the virus spreads mostly through the air. It causes some symptoms in the affected person. COVID-19 symptoms are quite variable, ranging from none to severe sickness. As a result, the fuzzy method is seen favourably as a tool for determining the severity of a person’s COVID-19 sickness. However, when applied to a large situation, manually generating a fuzzy parameter is challenging. This could be because of the identification of a large number of fuzzy parameters. A mechanism, such as an automatic procedure, is consequently required to identify the right fuzzy parameters. The metaheuristic algorithm is regarded as a viable strategy. Five meta-heuristic algorithms were analyzed and utilized in this article to classify the severity of COVID-19 sickness data. The performance of the five meta-heuristic algorithms was evaluated using the COVID-19 symptoms dataset. The COVID-19 symptom dataset was created in accordance with WHO and the Indian ministry of health and family welfare criteria. The findings provide the average classification accuracy for each approach.

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“…The internet of things (IoT) technology is able to monitor and control many smart devices remotely. Many IoT based online and remote monitoring systems has been developed by researcher [30]- [38] such as: i) object monitoring [31], [39]; ii) parking space monitoring and management [32]; iii) environmental monitoring [33], [36]; 4) electricity power consumption monitoring [35]; and 5) Body health monitoring [30], [37]. Most of the developed device is using NodeMCU ESP8266 for the main processor and Wi-Fi provider because of the low-cost and low-power consumption module [31], [39]- [42].…”

Section: Introductionmentioning

confidence: 99%

Internet of things-based photovoltaics parameter monitoring system using NodeMCU ESP8266

Sutikno

Purnama

Pamungkas

et al. 2021

IJECE

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<span>The use of the internet of things (IoT) in solar photovoltaic (PV) systems is a critical feature for remote monitoring, supervising, and performance evaluation. Furthermore, it improves the long-term viability, consistency, efficiency, and system maintenance of energy production. However, previous researchers' proposed PV monitoring systems are relatively complex and expensive. Furthermore, the existing systems do not have any backup data, which means that the acquired data could be lost if the network connection fails. This paper presents a simple and low-cost IoT-based PV parameter monitoring system, with additional backup data stored on a microSD card. A NodeMCU ESP8266 development board is chosen as the main controller because it is a system-on-chip (SOC) microcontroller with integrated Wi-Fi and low-power support, all in one chip to reduce the cost of the proposed system. The solar irradiance, ambient temperature, PV output voltage and PV output current, are measured with photo-diodes, DHT22, impedance dividers and ACS712. While, the PV output power is a product of the PV voltage and PV current. ThingSpeak, an open-source software, is used as a cloud database and data monitoring tool in the form of interactive graphics. The results showed that the system was designed to be highly accurate, reliable, simple to use, and low-cost.</span>

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COVID-19 fever symptom detection based on IoT cloud

Cited by 25 publications

References 11 publications

IoT-based COVID-19 Patient Vital Sign Monitoring

IoT-based COVID-19 Patient Vital Sign Monitoring

Comparison of meta-heuristic algorithms for fuzzy modelling of COVID-19 illness’ severity classification

Internet of things-based photovoltaics parameter monitoring system using NodeMCU ESP8266

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