iNEMO : a multi-sensor real-time human activity monitoring system

With the campus competition held by ST Microelectronics, the iNEMO sensor is a unique evaluation and development tool that offers up to 10 degrees of freedom, using combinations of 3-axis linear acceleration, angular rate and motion sensing, managed by an STM32 32-bit microcontroller and would be de...

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Main Author: Mi, Ding.
Other Authors: School of Electrical and Electronic Engineering
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/53363
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-533632023-07-07T16:02:57Z iNEMO : a multi-sensor real-time human activity monitoring system Mi, Ding. School of Electrical and Electronic Engineering STMicroelectronics Prof Chen ShouShun DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering With the campus competition held by ST Microelectronics, the iNEMO sensor is a unique evaluation and development tool that offers up to 10 degrees of freedom, using combinations of 3-axis linear acceleration, angular rate and motion sensing, managed by an STM32 32-bit microcontroller and would be designed for such kind of innovative project to fulfill the modern technology application. This project aims to develop an wireless real-time human activity monitoring system which includes the functionality of human behavior analysis for paying close attention to elderly living alone people in Singapore. This project consists of two parts. One is on tracking and analyzing iNEMO sensor’s 3 axis data via Bluetooth wireless transmission method. Another one is real-time indoor human behavior monitoring application by using the methodology of computer vision on image processing area. I was assigned the second part for my final year project implementation. The real-time indoor human behavior monitoring application performs above expectation. The image segmentation, objects detection, tracking and recognition process are successfully working on multiple objects application within certain effective range. Besides, the data analysis of individual object is gained by implementing kalman filter. Although the overall project is working properly, there still needs some improvements on some aspects of this system. Bachelor of Engineering 2013-05-31T08:30:56Z 2013-05-31T08:30:56Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/53363 en Nanyang Technological University 78 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
Mi, Ding.
iNEMO : a multi-sensor real-time human activity monitoring system
description With the campus competition held by ST Microelectronics, the iNEMO sensor is a unique evaluation and development tool that offers up to 10 degrees of freedom, using combinations of 3-axis linear acceleration, angular rate and motion sensing, managed by an STM32 32-bit microcontroller and would be designed for such kind of innovative project to fulfill the modern technology application. This project aims to develop an wireless real-time human activity monitoring system which includes the functionality of human behavior analysis for paying close attention to elderly living alone people in Singapore. This project consists of two parts. One is on tracking and analyzing iNEMO sensor’s 3 axis data via Bluetooth wireless transmission method. Another one is real-time indoor human behavior monitoring application by using the methodology of computer vision on image processing area. I was assigned the second part for my final year project implementation. The real-time indoor human behavior monitoring application performs above expectation. The image segmentation, objects detection, tracking and recognition process are successfully working on multiple objects application within certain effective range. Besides, the data analysis of individual object is gained by implementing kalman filter. Although the overall project is working properly, there still needs some improvements on some aspects of this system.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Mi, Ding.
format Final Year Project
author Mi, Ding.
author_sort Mi, Ding.
title iNEMO : a multi-sensor real-time human activity monitoring system
title_short iNEMO : a multi-sensor real-time human activity monitoring system
title_full iNEMO : a multi-sensor real-time human activity monitoring system
title_fullStr iNEMO : a multi-sensor real-time human activity monitoring system
title_full_unstemmed iNEMO : a multi-sensor real-time human activity monitoring system
title_sort inemo : a multi-sensor real-time human activity monitoring system
publishDate 2013
url http://hdl.handle.net/10356/53363
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