Please use this identifier to cite or link to this item: http://dspace.aiub.edu:8080/jspui/handle/123456789/863
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dc.contributor.authorPaul, Sanjay Kumar-
dc.contributor.authorShakil, Whakil Ahamed-
dc.contributor.authorRahman, Md Samiur-
dc.contributor.authorRahman, Midhat-
dc.contributor.authorAlam, Nuzat Nuary-
dc.date.accessioned2023-01-28T07:59:59Z-
dc.date.available2023-01-28T07:59:59Z-
dc.date.issued2023-01-18-
dc.identifier.urihttp://dspace.aiub.edu:8080/jspui/handle/123456789/863-
dc.descriptionCapstone Project Book 2022.2.8en_US
dc.description.abstractDementia has become a serious public health concern owing to its high incidence and effects on an aging population. Psychosocial interventions that increase cognitive function have been developed in recent decades. These treatments try to slow dementia's progression and promote healthy aging. This design provides an IOT-based safety hand for indoor and outdoor fall detection. The system incorporates fall detection, communication, notifications, and emergency medical aid. GPS helps caregivers find patients. Tri-axial accelerometers are used to study falls. When a fall is detected and the device detects an unconscious person, emergency contacts are called until someone responds. If no one replies within a specific time, the system calls for help. Even if the person has not fallen, he/she may press SOS to get help. A voice assistant recalls of routine, medicine, etc. This device contains a camera so that relatives or caretakers can watch over his or her activities.en_US
dc.publisher“Faculty of Engineering, American International University – Bangladeshen_US
dc.relation.ispartofseries2022.2;2022.2.8-
dc.title​​Real Time Dementia Care and Fall Detection Device for Elderly​en_US
dc.typeThesisen_US
Appears in Collections:Capstone Project Books

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