Internet of Sensing Things-Based Machine Learning Approach to Predict Parkinson

dc.contributor.authorAfroz, Sohana
dc.contributor.authorUllah Akhund, Tajim Md. Niamat
dc.contributor.authorKhan, Tarikuzzaman
dc.contributor.authorHasan, Md. Umaid
dc.contributor.authorJesmin, Rashida
dc.contributor.authorSarker, M. Mesbahuddin
dc.date.accessioned2026-04-05T04:26:10Z
dc.date.available2026-04-05T04:26:10Z
dc.date.issued2023-09-15
dc.descriptionConference Paper
dc.description.abstractWith the help of the Internet of things, therapeutic science has progressed surprisingly. Lots of elderly individuals are affected by Parkinson’s disease. This work proposed an Internet of sensing things-based system to collect data from Parkinson’s affected people analyze the collected data in a cloud server with machine learning algorithms and predict the condition of the patient. Multiple types of sensors are used and tested. Micro-controllers are used to collect data from sensors and send them to a cloud server. Then, multiple machine learning algorithms are used to predict the patient’s condition. Results between several methods are also compared.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/16563
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/16563
dc.language.isoen_US
dc.sourceDIU Institutional Repository
dc.subjectInternet of things (IoT)
dc.subjectParkinson prediction
dc.subjectInternet of sensing things (IoST)
dc.subjectMachine learning (ML)
dc.subjectNeurodegenerative disorder (NDD)
dc.titleInternet of Sensing Things-Based Machine Learning Approach to Predict Parkinson
dc.typeOther

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