dc.contributor.advisor | Rabiul Alam, Dr. Md. Golam | |
dc.contributor.author | Abedin, Minhajul | |
dc.contributor.author | Ahad, Mohammad Abdul | |
dc.contributor.author | Hasan-Ul-Banna, A.B.M | |
dc.contributor.author | Khan, Nibraz | |
dc.contributor.author | Hossain, Ashfaq | |
dc.date.accessioned | 2023-03-28T06:40:01Z | |
dc.date.available | 2023-03-28T06:40:01Z | |
dc.date.copyright | 2022 | |
dc.date.issued | 2022-09 | |
dc.identifier.other | ID: 18301224 | |
dc.identifier.other | ID: 18301248 | |
dc.identifier.other | ID: 18301143 | |
dc.identifier.other | ID: 18201057 | |
dc.identifier.other | ID: 18101658 | |
dc.identifier.uri | http://hdl.handle.net/10361/18028 | |
dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. | en_US |
dc.description | Cataloged from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages 31-32). | |
dc.description.abstract | Alzheimer’s is a brain disorder that gradually deteriorates the brain functions of the
patients. As the disease progresses, victims start to lose their memory, thinking ability, eventually rendering them unable to perform basic tasks. They also face many
difficulties namely disorientation, wandering, aggression, insomnia, hallucination,
etc. What makes the situation worse is that when the caregivers try to help them
most of the time they tend not to cooperate. In this paper, we have designed an AI
that assists the sufferers in combating these issues by analyzing their environment,
daily routine, interests, behavioral patterns, and many more factors. Using computer vision we have created a face recognition framework that identifies individuals
in front of the patient & shows him/her their name, how they are related, and some
photos & videos of them together. We also used an object detection system that
helps prevent wandering by constantly monitoring the surroundings of the patient
& notifying the caretakers about items such as keys, shoes, handbags, doors etc
that could influence the patient to leave the house. The AI is instructed to alarm
the attendant continuously if the patient somehow succeeds to go beyond the safe
area. This feature allows the caregivers some free time as they don’t need to monitor the patients 24/7 anymore. The face recognition framework achieves accuracy
of 97.44% and the object detection system has mAP of 72.3% that uses YOLOv7
model. Thus, this study tries to achieve its goal to make life comparatively easier for
the patients & the caregivers by making the patients self-dependent & discharging
the attendants from some of their tasks. | en_US |
dc.description.statementofresponsibility | Minhajul Abedin | |
dc.description.statementofresponsibility | Mohammad Abdul Ahad | |
dc.description.statementofresponsibility | A.B.M Hasan-Ul-Banna | |
dc.description.statementofresponsibility | Nibraz Khan | |
dc.description.statementofresponsibility | Ashfaq Hossain | |
dc.format.extent | 32 pages | |
dc.language.iso | en | en_US |
dc.publisher | Brac University | en_US |
dc.rights | Brac 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.subject | Alzheimer’s Disease | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | Object Detection | en_US |
dc.subject | Face Recognition | en_US |
dc.subject | Face Detection | en_US |
dc.subject | Face Embedding | en_US |
dc.subject | Face Classification | en_US |
dc.subject | YOLOv4 | en_US |
dc.subject | YOLOv7 | en_US |
dc.subject | MTCNN | en_US |
dc.subject | FaceNet | en_US |
dc.subject | SVC | en_US |
dc.subject | RFs | en_US |
dc.subject.lcsh | Alzheimer’s disease | |
dc.title | An ambient assisted living system for Alzheimer’s patients | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, Brac University | |
dc.description.degree | B. Computer Science | |