Das, AnindyaNayeem, ZannatunFaysal, Abu SalehHimu, Fardoush HassanSiam, Tanvinur Rahman2026-07-292026-07-292021-03-27A. Das, Z. Nayeem, A. S. Faysal, F. H. Himu and T. R. Siam, "Health Monitoring IoT Device with Risk Prediction using Cloud Computing and Machine Learning," 2021 National Computing Colleges Conference (NCCC), Taif, Saudi Arabia, 2021, pp. 1-6, doi: 10.1109/NCCC49330.2021.9428798.97817281671902-s2.0-85106592316https://hdl.handle.net/10361/28673Health conditions also stay concealed because of the absence of daily health checkups. Often such issues add up to a significant safety threat that stays concealed until it is always too late. So we have come up with a series of ideas that can address and to some extent solve the above stated problems. Our proposed system will continuously track body vitals, submit data to approved doctors across the cloud, and alert doctors to patients of the threat. To incorporate the above-mentioned solutions, we are developing an IoT system that interfaces multiple sensors to a microcomputer and sends the data gathered to a cloud server for further exploitation through Machine Learning. After analysis, if the doctor feels there is any risk of health hazard to the patient, he/she can send in the notification of hazard through our proposed device.6 pagesen-USfalseCloud serverHealth issueIoTMachine learningInformation storage and retrieval systems.Internet of things.Machine learning.Conference Proceeding10.1109/NCCC49330.2021.9428798