Please use this identifier to cite or link to this item:
Title: LECABot, mini robot companion for elderly
Authors: Low, Javier Tian Sheng
Keywords: Engineering::Computer science and engineering
Issue Date: 2020
Publisher: Nanyang Technological University
Abstract: Aging population has brought about a significant social problem for modern day society. Due to the advancement of healthcare, people tend to live longer than ever before. As the aging population problem worsens, the amount of elderly living alone has seen an all time high. Living alone has its own set of implications on an individual’s physical well being and mental health such as development of chronic diseases and mental illnesses due to loneliness. With technology evolving daily to become more accessible and user-friendly to the general public, the relevance of technology being implemented in our day to day lives has become more applicable. Robot companions leverages the power of technology to tackle the issue of loneliness by providing companionship for the elderly. There are various examples of elderly robot companions currently available in the market but they are either using proprietary technology or not cost-friendly to be implemented in a large scale environment. LECABot (also known as Lifelong Elderly Companion Assistant Bot) aims to set a standard by using efficient and affordable hardware bundled with open-source and easy to understand software so that every elderly would have access to a robot companion and help in the cause of combating loneliness. Using mBot and Raspberry Pi 3 B+, features include • Google Assistant to allow voice interaction with the elderly • mBot to connect and control the various hardware components of the robot • OpenCV to enable facial recognition and active tracking of elderly
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
  Restricted Access
FYP Final Report29.61 MBAdobe PDFView/Open

Page view(s)

Updated on Dec 8, 2022

Download(s) 50

Updated on Dec 8, 2022

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.