Health monitoring IoT device with risk prediction using cloud computing and machine learning

bracu.type.groupResearch Publications
datacite.rightsMetadata Only
dc.contributor.authorDas, Anindya
dc.contributor.authorNayeem, Zannatun
dc.contributor.authorFaysal, Abu Saleh
dc.contributor.authorHimu, Fardoush Hassan
dc.contributor.authorSiam, Tanvinur Rahman
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2026-07-29T04:27:43Z
dc.date.available2026-07-29T04:27:43Z
dc.date.issued2021-03-27
dc.description.abstractHealth 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.versionPublished
dc.format.extent6 pages
dc.identifier.citationA. 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.doi10.1109/NCCC49330.2021.9428798
dc.identifier.issn9781728167190
dc.identifier.other2-s2.0-85106592316
dc.identifier.urihttps://hdl.handle.net/10361/28673
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.hasversion10.1109/NCCC49330.2021.9428798
dc.relation.ispartofProceedings 2021 IEEE 4th National Computing Colleges Conference Nccc 2021
dc.relation.ispartofseriesProceedings 2021 IEEE 4th National Computing Colleges Conference Nccc 2021
dc.relation.urihttps://ieeexplore.ieee.org/document/9428798
dc.rightsfalse
dc.subjectCloud server
dc.subjectHealth issue
dc.subjectIoT
dc.subjectMachine learning
dc.subject.lcshInformation storage and retrieval systems.
dc.subject.lcshInternet of things.
dc.subject.lcshMachine learning.
dc.titleHealth monitoring IoT device with risk prediction using cloud computing and machine learning
dc.typeConference Proceeding
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.identifier.scopus-author-id57223991294
person.identifier.scopus-author-id57220548131
person.identifier.scopus-author-id57223963145
person.identifier.scopus-author-id57223982215
person.identifier.scopus-author-id57223973520

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Demo.jpg
Size:
27.28 KB
Format:
Joint Photographic Experts Group/JPEG File Interchange Format (JFIF)

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: