An IoT-based ambient assisted living for elderly care and monitoring in COVID-19 pandemic using arti cial intelligence and deep learning
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
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| التنسيق: | أطروحة |
| اللغة: | English |
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Brac University
2021
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/10361/15024 |
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10361-15024 |
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10361-150242022-01-26T10:08:22Z An IoT-based ambient assisted living for elderly care and monitoring in COVID-19 pandemic using arti cial intelligence and deep learning Bhowmick, Shovon Ferdous, Tarik Momtaz, Raihan Alam, Md. Golam Rabiul Department of Computer Science and Engineering, Brac University COVID-19 Deep Learning Arti cial Intelligence Sensor Linear Regression Analysis Hidden Markov Model XGBoost Raspberry Pi ESP32 SVM COVID-19 (Disease) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (page 50-54). In late 2019, a novel Coronavirus broke out from China, which has dispersed all over the globe and has taken away countless lives. Despite the fact that every person is at risk of getting infected with the virus, older people are more likely to fall victim to the virus due to their declining immune systems. Although there has been signi cant development of vaccines, it is seen that the mutation of the COVID-19 has made it tough to control with the medication available. Due to an uncountable number of Coronavirus strains, many countries are now facing the second wave of the pandemic. This disease is very contagious. Assisted living technologies are evolving with time to give people a better life. This technology can be used for older people in Coronavirus pandemic situations. Most of them have physical and cognitive impairments and face immense challenges in their day-to-day life. Older people are vulnerable to disease, and even simple disease can worsen their health. If our older people stay healthy and safe, our world would be a better place. In this paper, we have proposed an IoT-architectured system incorporated with Arti cial intelligence and deep learning that can help diagnose a disease of our beloved aged people. The proposed architecture will collect all the data from di erent medical IoT sensors and relay them to the cloud, where the system will process and help us monitor the health of older people. This information will be seen from a dedicated dashboard. The system will be able to predict the possible COVID-19 disease that an elderly person may su er in the near future. We cannot imagine a world without our dearest older people, and the chances of the next pandemic cannot be eliminated either. In order to be prepared for any future pandemic, this type of system will be bene cial. Shovon Bhowmick TAREK FERDOUS RAIHAN MOMTAZ B. Computer Science 2021-09-16T18:57:25Z 2021-09-16T18:57:25Z 2021 2021-06 Thesis ID 17101208 ID 17101491 ID 17101196 http://hdl.handle.net/10361/15024 en 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. 54 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
COVID-19 Deep Learning Arti cial Intelligence Sensor Linear Regression Analysis Hidden Markov Model XGBoost Raspberry Pi ESP32 SVM COVID-19 (Disease) |
| spellingShingle |
COVID-19 Deep Learning Arti cial Intelligence Sensor Linear Regression Analysis Hidden Markov Model XGBoost Raspberry Pi ESP32 SVM COVID-19 (Disease) Bhowmick, Shovon Ferdous, Tarik Momtaz, Raihan An IoT-based ambient assisted living for elderly care and monitoring in COVID-19 pandemic using arti cial intelligence and deep learning |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. |
| author2 |
Alam, Md. Golam Rabiul |
| author_facet |
Alam, Md. Golam Rabiul Bhowmick, Shovon Ferdous, Tarik Momtaz, Raihan |
| format |
Thesis |
| author |
Bhowmick, Shovon Ferdous, Tarik Momtaz, Raihan |
| author_sort |
Bhowmick, Shovon |
| title |
An IoT-based ambient assisted living for elderly care and monitoring in COVID-19 pandemic using arti cial intelligence and deep learning |
| title_short |
An IoT-based ambient assisted living for elderly care and monitoring in COVID-19 pandemic using arti cial intelligence and deep learning |
| title_full |
An IoT-based ambient assisted living for elderly care and monitoring in COVID-19 pandemic using arti cial intelligence and deep learning |
| title_fullStr |
An IoT-based ambient assisted living for elderly care and monitoring in COVID-19 pandemic using arti cial intelligence and deep learning |
| title_full_unstemmed |
An IoT-based ambient assisted living for elderly care and monitoring in COVID-19 pandemic using arti cial intelligence and deep learning |
| title_sort |
iot-based ambient assisted living for elderly care and monitoring in covid-19 pandemic using arti cial intelligence and deep learning |
| publisher |
Brac University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/15024 |
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