Elderly assisted living system

• Main Author: Muhammad Amirun Fariandie Jumri
• Other Authors: Law Choi Look
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2020
• Subjects: Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/145139
• Institution: Nanyang Technological University

Singapore is currently facing an ageing population whereby the old-age support ratio (OASR) in Singapore had decreased from 7.4 in 2010 to 4.3 in 2020. In addition, elderly aged 65 years and above have higher risks of being diagnosed with eye illness and/or experience deteriorating eyesight over time. Hence, the aim of this project is to develop a web server based system for elderly assisted living which would also involve a python implementation of machine learning technology to assist the elderly to switch on and off the lights automatically by anticipating the needs of the elderly. This project was carried out in two phases - Phase I and Phase 2. A Decawave software was used in Phase I and the implementation of machine learning was carried out in Phase II. This project revealed that the elderly assisted living system could be used to predict the lighting in an area (i.e. living room, dining room, kitchen etc.) in a household. However, this system could not be easily implemented. This is because the positioning of the anchor in the floor plan has to adjusted manually hence it is not user-friendly.