Exploration study of 60 GHz radar sensor for radar assisted living

Millimeter wave (mmWave) radar is an emerging technology with wide applications. As the world's population ages, there is an increasing demand for using mmWave radar for ambient assisted living, especially in living and working environment to provide care with independence for a growing elderly...

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Main Author: Zhao, Ziyue
Other Authors: Lu Yilong
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
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Online Access:https://hdl.handle.net/10356/158098
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1580982023-07-07T19:30:25Z Exploration study of 60 GHz radar sensor for radar assisted living Zhao, Ziyue Lu Yilong School of Electrical and Electronic Engineering EYLU@ntu.edu.sg Engineering::Electrical and electronic engineering::Antennas, wave guides, microwaves, radar, radio Millimeter wave (mmWave) radar is an emerging technology with wide applications. As the world's population ages, there is an increasing demand for using mmWave radar for ambient assisted living, especially in living and working environment to provide care with independence for a growing elderly population. In addition, research show that there is a close relation between the sleep state of people and their physical and psychological health. then it is particularly important to pay attention to the sleep state of the elderly. The project is divided into 3 parts. The first part focuses on radar concepts, the knowledge of the radar hardware, radar environment setup and software installation and testing. The second part is radar data acquisition. I will use 60 GHz radar sensor to collect the data of the radar to the target and the action during simulated sleep, including lying down, lying on the side and rolling over etc. In the research of data visualization, I also used MATLAB to assist. The third part is processing and analyzing the radar data through python program. In this part we use convolutional neural networks (CNN) which is a type of deep learning model to analyze and test the data of actions. The ultimate goal is to realize the sleep motion recognition solution into the Raspberry Pi, eliminating the need for an external laptop or computer to increase portability realize the processing on the Raspberry Pi and improve portability. This report also contains the introduction of the Raspberry Pi. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-29T12:27:38Z 2022-05-29T12:27:38Z 2022 Final Year Project (FYP) Zhao, Z. (2022). Exploration study of 60 GHz radar sensor for radar assisted living. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158098 https://hdl.handle.net/10356/158098 en P3044-202 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering::Antennas, wave guides, microwaves, radar, radio
spellingShingle Engineering::Electrical and electronic engineering::Antennas, wave guides, microwaves, radar, radio
Zhao, Ziyue
Exploration study of 60 GHz radar sensor for radar assisted living
description Millimeter wave (mmWave) radar is an emerging technology with wide applications. As the world's population ages, there is an increasing demand for using mmWave radar for ambient assisted living, especially in living and working environment to provide care with independence for a growing elderly population. In addition, research show that there is a close relation between the sleep state of people and their physical and psychological health. then it is particularly important to pay attention to the sleep state of the elderly. The project is divided into 3 parts. The first part focuses on radar concepts, the knowledge of the radar hardware, radar environment setup and software installation and testing. The second part is radar data acquisition. I will use 60 GHz radar sensor to collect the data of the radar to the target and the action during simulated sleep, including lying down, lying on the side and rolling over etc. In the research of data visualization, I also used MATLAB to assist. The third part is processing and analyzing the radar data through python program. In this part we use convolutional neural networks (CNN) which is a type of deep learning model to analyze and test the data of actions. The ultimate goal is to realize the sleep motion recognition solution into the Raspberry Pi, eliminating the need for an external laptop or computer to increase portability realize the processing on the Raspberry Pi and improve portability. This report also contains the introduction of the Raspberry Pi.
author2 Lu Yilong
author_facet Lu Yilong
Zhao, Ziyue
format Final Year Project
author Zhao, Ziyue
author_sort Zhao, Ziyue
title Exploration study of 60 GHz radar sensor for radar assisted living
title_short Exploration study of 60 GHz radar sensor for radar assisted living
title_full Exploration study of 60 GHz radar sensor for radar assisted living
title_fullStr Exploration study of 60 GHz radar sensor for radar assisted living
title_full_unstemmed Exploration study of 60 GHz radar sensor for radar assisted living
title_sort exploration study of 60 ghz radar sensor for radar assisted living
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/158098
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