Health monitoring IoT device with risk prediction using cloud computing and machine learning
| bracu.type.group | Research Publications | |
| datacite.rights | Metadata Only | |
| dc.contributor.author | Das, Anindya | |
| dc.contributor.author | Nayeem, Zannatun | |
| dc.contributor.author | Faysal, Abu Saleh | |
| dc.contributor.author | Himu, Fardoush Hassan | |
| dc.contributor.author | Siam, Tanvinur Rahman | |
| dc.contributor.department | Department of Computer Science and Engineering | |
| dc.date.accessioned | 2026-07-29T04:27:43Z | |
| dc.date.available | 2026-07-29T04:27:43Z | |
| dc.date.issued | 2021-03-27 | |
| dc.description.abstract | Health 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. | |
| dc.description.version | Published | |
| dc.format.extent | 6 pages | |
| dc.identifier.citation | A. 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. | |
| dc.identifier.doi | 10.1109/NCCC49330.2021.9428798 | |
| dc.identifier.issn | 9781728167190 | |
| dc.identifier.other | 2-s2.0-85106592316 | |
| dc.identifier.uri | https://hdl.handle.net/10361/28673 | |
| dc.language.iso | en_US | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.relation.hasversion | 10.1109/NCCC49330.2021.9428798 | |
| dc.relation.ispartof | Proceedings 2021 IEEE 4th National Computing Colleges Conference Nccc 2021 | |
| dc.relation.ispartofseries | Proceedings 2021 IEEE 4th National Computing Colleges Conference Nccc 2021 | |
| dc.relation.uri | https://ieeexplore.ieee.org/document/9428798 | |
| dc.rights | false | |
| dc.subject | Cloud server | |
| dc.subject | Health issue | |
| dc.subject | IoT | |
| dc.subject | Machine learning | |
| dc.subject.lcsh | Information storage and retrieval systems. | |
| dc.subject.lcsh | Internet of things. | |
| dc.subject.lcsh | Machine learning. | |
| dc.title | Health monitoring IoT device with risk prediction using cloud computing and machine learning | |
| dc.type | Conference Proceeding | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.identifier.scopus-author-id | 57223991294 | |
| person.identifier.scopus-author-id | 57220548131 | |
| person.identifier.scopus-author-id | 57223963145 | |
| person.identifier.scopus-author-id | 57223982215 | |
| person.identifier.scopus-author-id | 57223973520 |