Please use this identifier to cite or link to this item: http://tainguyenso.dut.udn.vn/handle/DUT/4140
DC FieldValueLanguage
dc.contributor.advisorPhạm, Văn Tuấn, PGS.TS
dc.contributor.advisorNguyễn, Lê Hòa, TS.
dc.contributor.advisorLê, Trung Phong
dc.contributor.authorNguyễn, Thanh Hùng
dc.contributor.authorTạ, Quốc Khánh
dc.date.accessioned2024-11-06T05:21:32Z-
dc.date.available2024-11-06T05:21:32Z-
dc.date.issued2021
dc.identifier.urihttp://tainguyenso.dut.udn.vn/handle/DUT/4140-
dc.descriptionDA.FA.21.039; 89 trvi
dc.description.abstractIn such a fast-pacing and highly competitive society, the seniors are increasingly let unsupervised and not taken care of. This is especially true in developing and mass population countries, where either healthcare or money is simply not sufficient to support them. One of the most serious incidents that the elderly encounter is fall. Various injuries caused by fall significantly downplay the function of a elder’s body, shorten their ages, and if they cannot recover or there is no timely aid from others, they may have to lie on the spot for a long time, leading to dehydration, hypothermia and even death. According to WHO, 28% to 35% of seniors are prone to fall annually, the rate rises up to 32% to 42% if they are over 70-year-old [67] . Hence, we aim to provide an affordable and versatile solution for fall detection in medical wards or elderly care facilitiesvi
dc.language.isoenvi
dc.publisherTrường Đại học Bách khoa - Đại học Đà Nẵngvi
dc.subjectHệ thống nhúngvi
dc.subjectAutonomous Robotvi
dc.subjectDeep Learningvi
dc.titleAutonomous Robot for detecting and following Humans in Hospital powered by Deep Learningvi
dc.typeĐồ ánvi
item.cerifentitytypePublications-
item.openairetypeĐồ án-
item.grantfulltextrestricted-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextCó toàn văn-
item.languageiso639-1en-
Appears in Collections:DA.Hệ thống nhúng
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