Intelligent elderly care
This report shows how Modular Tracker device uses the Internet of Things (IoT) , tracking and monitoring system Technologies to determine the location and safety of the dementia patient elderly. The two major parts of the device are GPS Tracker and Fall Detector which are both made to use on the sin...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
Nanyang Technological University
2020
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/140685 |
| _version_ | 1811696215174152192 |
|---|---|
| author | Shiew, Wei Lun |
| author2 | Lee Peng Hin |
| author_facet | Lee Peng Hin Shiew, Wei Lun |
| author_sort | Shiew, Wei Lun |
| collection | NTU |
| description | This report shows how Modular Tracker device uses the Internet of Things (IoT) , tracking and monitoring system Technologies to determine the location and safety of the dementia patient elderly. The two major parts of the device are GPS Tracker and Fall Detector which are both made to use on the single board computer Raspberry pi. The implementation and testing of the two major parts are divided into five stages. The implementation section for the five stages include the methods used and approaches to develop the modules for the two major parts. The testing section for the 5 major stages will include the testing methods used for each stage and the approached to solve an individual stage issue. This device will constantly send updates of location and safety status of the patients up onto the IoT dashboard for family member constant monitor |
| first_indexed | 2024-10-01T07:35:49Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/140685 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:35:49Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1406852023-07-07T18:03:58Z Intelligent elderly care Shiew, Wei Lun Lee Peng Hin School of Electrical and Electronic Engineering Lee Peng Hin EPHLee@ntu.edu.sg Engineering::Electrical and electronic engineering This report shows how Modular Tracker device uses the Internet of Things (IoT) , tracking and monitoring system Technologies to determine the location and safety of the dementia patient elderly. The two major parts of the device are GPS Tracker and Fall Detector which are both made to use on the single board computer Raspberry pi. The implementation and testing of the two major parts are divided into five stages. The implementation section for the five stages include the methods used and approaches to develop the modules for the two major parts. The testing section for the 5 major stages will include the testing methods used for each stage and the approached to solve an individual stage issue. This device will constantly send updates of location and safety status of the patients up onto the IoT dashboard for family member constant monitor Bachelor of Engineering (Electrical and Electronic Engineering) 2020-06-01T07:20:10Z 2020-06-01T07:20:10Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/140685 en A1003-191 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Shiew, Wei Lun Intelligent elderly care |
| title | Intelligent elderly care |
| title_full | Intelligent elderly care |
| title_fullStr | Intelligent elderly care |
| title_full_unstemmed | Intelligent elderly care |
| title_short | Intelligent elderly care |
| title_sort | intelligent elderly care |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/140685 |
| work_keys_str_mv | AT shiewweilun intelligentelderlycare |