{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T21:17:30Z","timestamp":1790284650612,"version":"4.1.0"},"reference-count":25,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T00:00:00Z","timestamp":1782432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004242","name":"Princess Nourah bint Abdulrahman University","doi-asserted-by":"publisher","award":["PNURSP2026R209"],"award-info":[{"award-number":["PNURSP2026R209"]}],"id":[{"id":"10.13039\/501100004242","id-type":"DOI","asserted-by":"publisher"}]},{"award":["PNURSP2026R209"],"award-info":[{"award-number":["PNURSP2026R209"]}],"id":[{"id":"https:\/\/ror.org\/05b0cyh02","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The COVID-19 pandemic exposed critical vulnerabilities in healthcare systems worldwide, placing healthcare workers (HCWs) at severe infection risk through direct patient contact. Epidemiological data confirm that HCWs were approximately seven times more likely to develop severe COVID-19 than other occupations, with over 7000 HCW deaths recorded globally by mid-2020. This paper presents the design and laboratory proof-of-concept validation of an IoT-based remote patient-monitoring system prototype\u2014the IoT-Based Isolation Ward Monitoring System Prototype\u2014designed to eliminate unnecessary patient-to-HCW physical contact while maintaining continuous, real-time physiological surveillance. The system integrates multi-sensor hardware comprising an AD8232 ECG module, a MAX30100 pulse oximeter, an NTC thermistor, and an MQ-135 CO2 sensor. These sensors interface with an Arduino UNO for data acquisition, while localized edge computing is executed on a Raspberry Pi 3B. A convolutional neural network (CNN) trained on the MIT-BIH Arrhythmia Database classifies heartbeats into five distinct categories. By utilizing SMOTE resampling on 109,446 samples, the network achieves an on-device inference latency of under 200 ms. The sensor data are transmitted to a Firebase Realtime Database via an authenticated REST API, which synchronizes data across dual front-end interfaces: a LabVIEW desktop dashboard for clinical oversight and a cross-platform Flutter mobile application for mobile monitoring. End-to-end technical validation under controlled laboratory conditions confirmed round-trip cloud latencies between 300 and 800 ms, error-free threshold alert generation, and sub-second latency for the integrated chat utility. The proposed system uniquely combines hardware sensing, ML-based ECG classification, cloud storage, a LabVIEW physician dashboard, and bidirectional doctor\u2013patient mobile communication into a single unified, low-cost platform.<\/jats:p>","DOI":"10.3390\/s26134065","type":"journal-article","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T05:49:33Z","timestamp":1782712173000},"page":"4065","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["IoT-Based Isolation Ward Monitoring System Prototype"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8621-4410","authenticated-orcid":false,"given":"Mohamed A.","family":"Torad","sequence":"first","affiliation":[{"name":"Department of Electronics and Communication Engineering, Higher Technological Institute (HTI), 10th of Ramadan City 44634, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4170-6694","authenticated-orcid":false,"given":"Ahmed A. M.","family":"Torad","sequence":"additional","affiliation":[{"name":"Department of Physical Therapy and Health Rehabilitation, Jouf University, Sakaka 72341, Saudi Arabia"},{"name":"Department of Basic Sciences, Faculty of Physical Therapy, Kafrelsheikh University, Kafrelsheikh 33516, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9080-5061","authenticated-orcid":false,"given":"Mona Mohamed","family":"Taha","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, College of Health and Rehabilitation Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9390-5524","authenticated-orcid":false,"given":"Eslam Samy","family":"El-Mokadem","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering, Higher Technological Institute (HTI), 10th of Ramadan City 44634, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1109\/MPRV.2021.3066825","article-title":"TELECOVID: Remote Vital Signs Monitoring of COVID-19 Risk Patients in Home Isolation with an In-Ear Wearable","volume":"20","author":"Baldinger","year":"2021","journal-title":"IEEE Pervasive Comput."},{"key":"ref_2","unstructured":"World Health Organization (2020). 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