{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T20:15:56Z","timestamp":1768421756432,"version":"3.49.0"},"reference-count":31,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,5]],"date-time":"2022-02-05T00:00:00Z","timestamp":1644019200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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\u2019s health condition remotely. Every layer has specific functionality in the COVID-19 symptoms\u2019 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.<\/jats:p>","DOI":"10.3390\/s22031205","type":"journal-article","created":{"date-parts":[[2022,2,6]],"date-time":"2022-02-06T20:40:18Z","timestamp":1644180018000},"page":"1205","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":49,"title":["Remotely Monitoring COVID-19 Patient Health Condition Using Metaheuristics Convolute Networks from IoT-Based Wearable Device Health Data"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5777-9428","authenticated-orcid":false,"given":"Mustafa Musa","family":"Jaber","sequence":"first","affiliation":[{"name":"Department of Computer Science, Dijlah University College, Baghdad 10022, Iraq"},{"name":"Department of Medical Instruments Engineering Techniques, Al-Farahidi University, Baghdad 10022, Iraq"}]},{"given":"Thamer","family":"Alameri","sequence":"additional","affiliation":[{"name":"Police Academy, Baghdad 10022, Iraq"}]},{"given":"Mohammed Hasan","family":"Ali","sequence":"additional","affiliation":[{"name":"Computer Techniques Engineering Department, Faculty of Information Technology, Imam Ja\u2019afar Al-Sadiq University, Nasiriyah 64001, Iraq"},{"name":"College of Computer Science and Mathematics, University of Kufa, Najaf 540011, Iraq"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4672-8991","authenticated-orcid":false,"given":"Adi","family":"Alsyouf","sequence":"additional","affiliation":[{"name":"Department of Managing Health Services and Hospitals, Faculty of Business Rabigh, College of Business (COB), King Abdulaziz University, Jeddah 21991, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2698-8101","authenticated-orcid":false,"given":"Mohammad","family":"Al-Bsheish","sequence":"additional","affiliation":[{"name":"Healthcare Administration Department, Batterjee Medical College, Jeddah 21442, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3012-5766","authenticated-orcid":false,"given":"Badr K.","family":"Aldhmadi","sequence":"additional","affiliation":[{"name":"Department of Health Management, College of Public Health and Health Informatics, University of Ha\u2019il, Ha\u2019il 81451, Saudi Arabia"}]},{"given":"Sarah Yahya","family":"Ali","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Dijlah University College, Baghdad 10022, Iraq"}]},{"given":"Sura Khalil","family":"Abd","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Dijlah University College, Baghdad 10022, Iraq"},{"name":"Department of Computer Science, Al-Turath University College, Baghdad 10021, Iraq"}]},{"given":"Saif Mohammed","family":"Ali","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Dijlah University College, Baghdad 10022, Iraq"}]},{"given":"Waleed","family":"Albaker","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam 34212, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7748-2069","authenticated-orcid":false,"given":"Mu\u2019taman","family":"Jarrar","sequence":"additional","affiliation":[{"name":"Medical Education Department, King Fahd Hospital of the University, Al-Khobar 34445, Saudi Arabia"},{"name":"Vice Deanship for Quality and Development, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam 34212, Saudi Arabia"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1007\/s11125-020-09464-3","article-title":"Education and the COVID-19 pandemic","volume":"49","author":"Daniel","year":"2020","journal-title":"Prospects"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"510","DOI":"10.1056\/NEJMp2008017","article-title":"Mental health and the COVID-19 pandemic","volume":"383","author":"Pfefferbaum","year":"2020","journal-title":"N. Engl. J. Med."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1080\/10408363.2020.1783198","article-title":"The COVID-19 pandemic","volume":"57","author":"Ciotti","year":"2020","journal-title":"Crit. Rev. Clin. Lab. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/s12652-017-0598-x","article-title":"Remote patient monitoring: A comprehensive study","volume":"10","author":"Malasinghe","year":"2019","journal-title":"J. Ambient Intell. Humaniz. Comput."},{"key":"ref_5","unstructured":"Archip, A., Botezatu, N., \u015eerban, E., Herghelegiu, P.-C., and Zal\u0103, A. (June, January 29). An IoT based system for remote patient monitoring. Proceedings of the 17th International Carpathian Control Conference (ICCC), High Tatras, Slovakia."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"27262","DOI":"10.1109\/ACCESS.2021.3058448","article-title":"An IoT-based healthcare platform for patients in ICU beds during the COVID-19 outbreak","volume":"9","author":"Aquino","year":"2021","journal-title":"IEEE Access"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Paganelli, A.I., Velmovitsky, P.E., Miranda, P., Branco, A., Alencar, P., Cowan, D., Endler, M., and Morita, P.P. (2021). A conceptual IoT-based early-warning architecture for remote monitoring of COVID-19 patients in wards and at home. Internet Things, 100399.","DOI":"10.1016\/j.iot.2021.100399"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Jaafari, S., Alhasani, A., and Almutairi, S.M. (2020, January 9\u201310). Certain Investigations on IoT system for COVID-19. Proceedings of the 2020 International Conference on Computing and Information Technology (ICCIT-1441), Tabuk, Saudi Arabia.","DOI":"10.1109\/ICCIT-144147971.2020.9213760"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/j.jobcr.2021.01.015","article-title":"Internet of Things (IoT) enabled healthcare helps to take the challenges of COVID-19 Pandemic","volume":"11","author":"Javaid","year":"2021","journal-title":"J. Oral Biol. Craniofacial Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"110071","DOI":"10.1016\/j.chaos.2020.110071","article-title":"Recognition of COVID-19 disease from X-ray images by hybrid model consisting of 2D curvelet transform, chaotic salp swarm algorithm and deep learning technique","volume":"140","author":"Altan","year":"2020","journal-title":"Chaos Solitons Fractals"},{"key":"ref_11","first-page":"11455","article-title":"Deep learning applications to combat the dissemination of COVID-19 disease: A review","volume":"24","author":"Alsharif","year":"2020","journal-title":"Eur. Rev. Med. Pharmacol. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"102518","DOI":"10.1016\/j.bspc.2021.102518","article-title":"Automatic detection of COVID-19 disease using U-Net architecture based fully convolutional network","volume":"67","author":"Kalane","year":"2021","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_13","first-page":"242","article-title":"Coronavirus Disease 2019 (COVID-19): Diagnosis and Management (narrative review)","volume":"42","year":"2020","journal-title":"Erciyes Med. J."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1159\/000515748","article-title":"Viral replication and antibody kinetics in the recognition of asymptomatic COVID-19 patients","volume":"66","author":"Rabaan","year":"2021","journal-title":"Chemotherapy"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"e00922-20","DOI":"10.1128\/mSphere.00922-20","article-title":"Descriptive, retrospective study of the clinical characteristics of asymptomatic COVID-19 patients","volume":"5","author":"Han","year":"2020","journal-title":"MSphere"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e00442-20","DOI":"10.1128\/mSphere.00442-20","article-title":"Asymptomatic COVID-19 Patients Can Contaminate Their Surroundings: An Environment Sampling Study","volume":"5","author":"Wei","year":"2020","journal-title":"mSphere"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Alam, T. (2021, November 25). Internet of Things and Blockchain-Based Framework for Coronavirus (COVID-19) Disease. Available online: https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3660503.","DOI":"10.2139\/ssrn.3660503"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"AlsAlsyouf, A., Masa\u2019deh, R.E., Albugami, M., Al-Bsheish, M., Lutfi, A., and Alsubahi, N. (2021). Risk of Fear and Anxiety in Utilising Health App Surveillance Due to COVID-19: Gender Differences Analysis. Risks, 9.","DOI":"10.3390\/risks9100179"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1109\/IOTM.0001.2000123","article-title":"Privacy-Aware Energy-Efficient Framework Using the Internet of Medical Things for COVID-19","volume":"3","author":"Deebak","year":"2020","journal-title":"IEEE Internet Things Mag."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"El-Rashidy, N., El-Sappagh, S., Islam, S.M., El-Bakry, H.M., and Abdelrazek, S. (2020). End-to-end deep learning framework for coronavirus (COVID-19) detection and monitoring. Electronics, 9.","DOI":"10.3390\/electronics9091439"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1109\/MNET.011.2000353","article-title":"B5G and Explainable Deep Learning Assisted Healthcare Vertical at the Edge: COVID-I9 Perspective","volume":"34","author":"Rahman","year":"2020","journal-title":"IEEE Netw."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Tan, L., Yu, K., Bashir, A.K., Cheng, X., Ming, F., Zhao, L., and Zhou, X. (2021). Toward real-time and efficient cardiovascular monitoring for COVID-19 patients by 5G-enabled wearable medical devices: A deep learning approach. Neural Comput. Appl., 1\u201314.","DOI":"10.1007\/s00521-021-06219-9"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"42483","DOI":"10.1109\/ACCESS.2021.3064826","article-title":"ANN Assisted-IoT enabled COVID-19 patient monitoring","volume":"9","author":"Rathee","year":"2021","journal-title":"IEEE Access"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"102149","DOI":"10.1016\/j.bspc.2020.102149","article-title":"An IoT-based framework for early identification and monitoring of COVID-19 cases","volume":"62","author":"Otoom","year":"2020","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"109761","DOI":"10.1016\/j.mehy.2020.109761","article-title":"COVIDiagnosis-Net: Deep Bayes-SqueezeNet based diagnosis of the coronavirus disease 2019 (COVID-19) from X-ray images","volume":"140","author":"Ucar","year":"2020","journal-title":"Med. Hypotheses"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Mukherjee, R., Kundu, A., Mukherjee, I., Gupta, D., Tiwari, P., Khanna, A., and Shorfuzzaman, M. (2021). IoT-cloud based healthcare model for COVID-19 detection: An enhanced k-Nearest Neighbour classifier based approach. Computing, 1\u201321.","DOI":"10.1007\/s00607-021-00951-9"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"103869","DOI":"10.1016\/j.compbiomed.2020.103869","article-title":"CovXNet: A multi-dilation convolutional neural network for automatic COVID-19 and other pneumonia detection from chest X-ray images with transferable multi-receptive feature optimisation","volume":"122","author":"Mahmud","year":"2020","journal-title":"Comput. Biol. Med."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Yang, F., He, S., Sadanand, S., Yusuf, A., and Bolic, M. (2022). Contactless Measurement of Vital Signs Using Thermal and RGB Cameras: A Study of COVID 19-Related Health Monitoring. Sensors, 22.","DOI":"10.3390\/s22020627"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Khan, I.U., Aslam, N., Anwar, T., Alsaif, H.S., Chrouf, S.M., Alzahrani, N.A., Alamoudi, F.A., Kamaleldin, M.M.A., and Awary, K.B. (2022). Using a Deep Learning Model to Explore the Impact of Clinical Data on COVID-19 Diagnosis Using Chest X-ray. Sensors, 22.","DOI":"10.3390\/s22020669"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"26001","DOI":"10.1007\/s11042-021-10781-8","article-title":"PPG-based human identification using Mel-frequency cepstral coefficients and neural networks","volume":"80","author":"Siam","year":"2021","journal-title":"Multimed. Tools. Appl."},{"key":"ref_31","unstructured":"(2021, November 21). Azure Open Datasets Documentation. Available online: https:\/\/docs.microsoft.com\/en-us\/azure\/open-datasets\/."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/3\/1205\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:14:31Z","timestamp":1760134471000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/3\/1205"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,5]]},"references-count":31,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["s22031205"],"URL":"https:\/\/doi.org\/10.3390\/s22031205","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,5]]}}}