Remotely Monitoring COVID-19 Patient Health Condition Using Metaheuristics Convolute Networks from IoT-Based Wearable Device Health Data
Today, COVID-19-patient health monitoring and management are major public health challenges for technologies. This research monitored COVID-19 patients by using the Internet of Things. IoT-based collected real-time GPS helps alert the patient automatically to reduce risk factors. Wearable IoT device...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/3/1205 |
| _version_ | 1797484572633464832 |
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| author | Mustafa Musa Jaber Thamer Alameri Mohammed Hasan Ali Adi Alsyouf Mohammad Al-Bsheish Badr K. Aldhmadi Sarah Yahya Ali Sura Khalil Abd Saif Mohammed Ali Waleed Albaker Mu’taman Jarrar |
| author_facet | Mustafa Musa Jaber Thamer Alameri Mohammed Hasan Ali Adi Alsyouf Mohammad Al-Bsheish Badr K. Aldhmadi Sarah Yahya Ali Sura Khalil Abd Saif Mohammed Ali Waleed Albaker Mu’taman Jarrar |
| author_sort | Mustafa Musa Jaber |
| collection | DOAJ |
| description | Today, COVID-19-patient health monitoring and management are major public health challenges for technologies. This research monitored COVID-19 patients by using the Internet of Things. IoT-based collected real-time GPS helps alert the patient automatically to reduce risk factors. Wearable IoT devices are attached to the human body, interconnected with edge nodes, to investigate data for making health-condition decisions. This system uses the wearable IoT sensor, cloud, and web layers to explore the patient’s health condition remotely. Every layer has specific functionality in the COVID-19 symptoms’ monitoring process. The first layer collects the patient health information, which is transferred to the second layer that stores that data in the cloud. The network examines health data and alerts the patients, thus helping users take immediate actions. Finally, the web layer notifies family members to take appropriate steps. This optimized deep-learning model allows for the management and monitoring for further analysis. |
| first_indexed | 2024-03-09T23:07:18Z |
| format | Article |
| id | doaj.art-db9bb8052abc46c88524d2e80c66fde7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T23:07:18Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-db9bb8052abc46c88524d2e80c66fde72023-11-23T17:52:14ZengMDPI AGSensors1424-82202022-02-01223120510.3390/s22031205Remotely Monitoring COVID-19 Patient Health Condition Using Metaheuristics Convolute Networks from IoT-Based Wearable Device Health DataMustafa Musa Jaber0Thamer Alameri1Mohammed Hasan Ali2Adi Alsyouf3Mohammad Al-Bsheish4Badr K. Aldhmadi5Sarah Yahya Ali6Sura Khalil Abd7Saif Mohammed Ali8Waleed Albaker9Mu’taman Jarrar10Department of Computer Science, Dijlah University College, Baghdad 10022, IraqPolice Academy, Baghdad 10022, IraqComputer Techniques Engineering Department, Faculty of Information Technology, Imam Ja’afar Al-Sadiq University, Nasiriyah 64001, IraqDepartment of Managing Health Services and Hospitals, Faculty of Business Rabigh, College of Business (COB), King Abdulaziz University, Jeddah 21991, Saudi ArabiaHealthcare Administration Department, Batterjee Medical College, Jeddah 21442, Saudi ArabiaDepartment of Health Management, College of Public Health and Health Informatics, University of Ha’il, Ha’il 81451, Saudi ArabiaDepartment of Computer Science, Dijlah University College, Baghdad 10022, IraqDepartment of Computer Science, Dijlah University College, Baghdad 10022, IraqDepartment of Computer Science, Dijlah University College, Baghdad 10022, IraqDepartment of Internal Medicine, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam 34212, Saudi ArabiaMedical Education Department, King Fahd Hospital of the University, Al-Khobar 34445, Saudi ArabiaToday, COVID-19-patient health monitoring and management are major public health challenges for technologies. This research monitored COVID-19 patients by using the Internet of Things. IoT-based collected real-time GPS helps alert the patient automatically to reduce risk factors. Wearable IoT devices are attached to the human body, interconnected with edge nodes, to investigate data for making health-condition decisions. This system uses the wearable IoT sensor, cloud, and web layers to explore the patient’s health condition remotely. Every layer has specific functionality in the COVID-19 symptoms’ monitoring process. The first layer collects the patient health information, which is transferred to the second layer that stores that data in the cloud. The network examines health data and alerts the patients, thus helping users take immediate actions. Finally, the web layer notifies family members to take appropriate steps. This optimized deep-learning model allows for the management and monitoring for further analysis.https://www.mdpi.com/1424-8220/22/3/1205COVID-19cloud computingdeep learninghealthcare dataIoT sensorswearable sensors |
| spellingShingle | Mustafa Musa Jaber Thamer Alameri Mohammed Hasan Ali Adi Alsyouf Mohammad Al-Bsheish Badr K. Aldhmadi Sarah Yahya Ali Sura Khalil Abd Saif Mohammed Ali Waleed Albaker Mu’taman Jarrar Remotely Monitoring COVID-19 Patient Health Condition Using Metaheuristics Convolute Networks from IoT-Based Wearable Device Health Data Sensors COVID-19 cloud computing deep learning healthcare data IoT sensors wearable sensors |
| title | Remotely Monitoring COVID-19 Patient Health Condition Using Metaheuristics Convolute Networks from IoT-Based Wearable Device Health Data |
| title_full | Remotely Monitoring COVID-19 Patient Health Condition Using Metaheuristics Convolute Networks from IoT-Based Wearable Device Health Data |
| title_fullStr | Remotely Monitoring COVID-19 Patient Health Condition Using Metaheuristics Convolute Networks from IoT-Based Wearable Device Health Data |
| title_full_unstemmed | Remotely Monitoring COVID-19 Patient Health Condition Using Metaheuristics Convolute Networks from IoT-Based Wearable Device Health Data |
| title_short | Remotely Monitoring COVID-19 Patient Health Condition Using Metaheuristics Convolute Networks from IoT-Based Wearable Device Health Data |
| title_sort | remotely monitoring covid 19 patient health condition using metaheuristics convolute networks from iot based wearable device health data |
| topic | COVID-19 cloud computing deep learning healthcare data IoT sensors wearable sensors |
| url | https://www.mdpi.com/1424-8220/22/3/1205 |
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