Location tracking using multi-sensor fusion and machine learning techniques

With the use of Global Positioning System (GPS), the precise location of any object or person can be determined accurately using satellite signals. However, GPS may not be useful when there are obstacles or building, in particular, in many indoor scenarios. Consequentially, an indoor location track...

Full description

Saved in:

Bibliographic Details
Main Author:	Tan, Wei Sheng
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/10356/145051
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-145051
record_format	dspace
spelling	sg-ntu-dr.10356-1450512023-07-07T17:16:23Z Location tracking using multi-sensor fusion and machine learning techniques Tan, Wei Sheng Law Choi Look School of Electrical and Electronic Engineering ECLLAW@ntu.edu.sg Engineering::Electrical and electronic engineering With the use of Global Positioning System (GPS), the precise location of any object or person can be determined accurately using satellite signals. However, GPS may not be useful when there are obstacles or building, in particular, in many indoor scenarios. Consequentially, an indoor location tracking system is necessary for determining position. With reliance on the technologies and sensors that are available, this project aims to develop an indoor positioning system that is independent of the GPS signal. This report highlights and describes the workings of inertial measurement unit sensors, as well as various machine learning algorithms required to implement an indoor positioning system. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-12-09T07:06:42Z 2020-12-09T07:06:42Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/145051 en 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
spellingShingle	Engineering::Electrical and electronic engineering Tan, Wei Sheng Location tracking using multi-sensor fusion and machine learning techniques
description	With the use of Global Positioning System (GPS), the precise location of any object or person can be determined accurately using satellite signals. However, GPS may not be useful when there are obstacles or building, in particular, in many indoor scenarios. Consequentially, an indoor location tracking system is necessary for determining position. With reliance on the technologies and sensors that are available, this project aims to develop an indoor positioning system that is independent of the GPS signal. This report highlights and describes the workings of inertial measurement unit sensors, as well as various machine learning algorithms required to implement an indoor positioning system.
author2	Law Choi Look
author_facet	Law Choi Look Tan, Wei Sheng
format	Final Year Project
author	Tan, Wei Sheng
author_sort	Tan, Wei Sheng
title	Location tracking using multi-sensor fusion and machine learning techniques
title_short	Location tracking using multi-sensor fusion and machine learning techniques
title_full	Location tracking using multi-sensor fusion and machine learning techniques
title_fullStr	Location tracking using multi-sensor fusion and machine learning techniques
title_full_unstemmed	Location tracking using multi-sensor fusion and machine learning techniques
title_sort	location tracking using multi-sensor fusion and machine learning techniques
publisher	Nanyang Technological University
publishDate	2020
url	https://hdl.handle.net/10356/145051
_version_	1772827401815851008

Location tracking using multi-sensor fusion and machine learning techniques

Similar Items