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...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
Nanyang Technological University
2020
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/145051 |
| _version_ | 1826123314283675648 |
|---|---|
| author | Tan, Wei Sheng |
| author2 | Law Choi Look |
| author_facet | Law Choi Look Tan, Wei Sheng |
| author_sort | Tan, Wei Sheng |
| collection | NTU |
| 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. |
| first_indexed | 2024-10-01T06:02:19Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/145051 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:02:19Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-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 |
| spellingShingle | Engineering::Electrical and electronic engineering Tan, Wei Sheng Location tracking using multi-sensor fusion and machine learning techniques |
| title | 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_short | Location tracking using multi-sensor fusion and machine learning techniques |
| title_sort | location tracking using multi sensor fusion and machine learning techniques |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/145051 |
| work_keys_str_mv | AT tanweisheng locationtrackingusingmultisensorfusionandmachinelearningtechniques |