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dc.contributor.advisorRhaman, Md. Khalilur
dc.contributor.authorIslam, Md. Nazmul
dc.contributor.authorAl-Amin, Md.
dc.contributor.authorHassan, Md. Zaed
dc.contributor.authorIslam, Tamzid
dc.date.accessioned2024-05-20T08:35:56Z
dc.date.available2024-05-20T08:35:56Z
dc.date.copyright©2024
dc.date.issued2024-01
dc.identifier.otherID: 19301033
dc.identifier.otherID: 19301028
dc.identifier.otherID: 19301024
dc.identifier.otherID: 19301050
dc.identifier.urihttp://hdl.handle.net/10361/22889
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 58-60).
dc.description.abstractThe increasing number of elderly individuals living alone has emerged as a pressing global concern. Our research aims to address this issue by developing advanced modules that can be integrated into a system that enhances the quality of life for older adults. The modules focus on medicine detection, fall detection, reminders for important tasks and events and providing companionship through friendly verbal interactions. Through the integration of cutting-edge deep learning techniques, diverse models and natural language processing (NLP), we have successfully designed an effective medication and well-being assistant. These modules use computer vision technology along with reinforced learning from human feedback and convolutional neural networks (CNNs) to reach our goal. The modules can be integrated into systems to empower elderly individuals to lead more active and fulfilling lives. Finally, this research contributes to the well-being and happiness of the elderly, highlighting the significance of comprehensive support systems in promoting their overall well-being.en_US
dc.description.statementofresponsibilityMd. Nazmul Islam
dc.description.statementofresponsibilityMd. Al-Amin
dc.description.statementofresponsibilityMd. Zaed Hassan
dc.description.statementofresponsibilityTamzid Islam
dc.format.extent72 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectCompanion systemen_US
dc.subjectDeep learningen_US
dc.subjectCNNen_US
dc.subjectReinforced learningen_US
dc.subjectNLPen_US
dc.subjectMedication habiten_US
dc.subject.lcshNatural language processing (Computer science)
dc.subject.lcshDeep learning (Machine learning)
dc.titleHealth trauma and well-being assistant for Bengali seniors in household: a multimodal approachen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB.Sc in Computer Science and Engineering


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