Inaudible echo-based indoor position recognition (part 2)

Indoor localization using mobile application has seen raised in demand in the market. Room Recognition using inaudible echo is one of the techniques for indoor localization. In addition, it is susceptible to phone orientation which had detrimental effect on room recognition accuracy. This project...

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Main Author: Eng, Yong Peng
Other Authors: Tan Rui
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
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Online Access:https://hdl.handle.net/10356/147999
https://doi.org/10.1145/3264945
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1479992021-04-22T02:50:51Z Inaudible echo-based indoor position recognition (part 2) Eng, Yong Peng Tan Rui School of Computer Science and Engineering tanrui@ntu.edu.sg Engineering::Computer science and engineering Indoor localization using mobile application has seen raised in demand in the market. Room Recognition using inaudible echo is one of the techniques for indoor localization. In addition, it is susceptible to phone orientation which had detrimental effect on room recognition accuracy. This project studies various methods to sense phone orientation in real-time to mitigate the impact of phone orientation on indoor position recognition. In this paper, we explore the characteristics of 3 orientation sensing sensors: accelerometer, gyroscope, and magnetometer. Each of the sensors is not perfect in determining the phone orientation but have certain benefits to compensate one another. The benefits of the 3 sensors will be combined using a sensor fusion algorithm to produce the best possible orientation estimation. While there are several ways to conduct sensor fusion, we will concentrate on using complementary filters in this project. Keywords: Indoor localization, Room recognition, Inaudible echo, Smartphone, Sensors, Phone orientation, Accelerometer, Gyroscope, Magnetometer, Sensor fusion, Complementary filter Bachelor of Engineering (Computer Science) 2021-04-22T02:50:50Z 2021-04-22T02:50:50Z 2021 Final Year Project (FYP) Eng, Y. P. (2021). Inaudible echo-based indoor position recognition (part 2). Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/147999 https://hdl.handle.net/10356/147999 en SCSE20-0074 https://doi.org/10.1145/3264945 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::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Eng, Yong Peng
Inaudible echo-based indoor position recognition (part 2)
description Indoor localization using mobile application has seen raised in demand in the market. Room Recognition using inaudible echo is one of the techniques for indoor localization. In addition, it is susceptible to phone orientation which had detrimental effect on room recognition accuracy. This project studies various methods to sense phone orientation in real-time to mitigate the impact of phone orientation on indoor position recognition. In this paper, we explore the characteristics of 3 orientation sensing sensors: accelerometer, gyroscope, and magnetometer. Each of the sensors is not perfect in determining the phone orientation but have certain benefits to compensate one another. The benefits of the 3 sensors will be combined using a sensor fusion algorithm to produce the best possible orientation estimation. While there are several ways to conduct sensor fusion, we will concentrate on using complementary filters in this project. Keywords: Indoor localization, Room recognition, Inaudible echo, Smartphone, Sensors, Phone orientation, Accelerometer, Gyroscope, Magnetometer, Sensor fusion, Complementary filter
author2 Tan Rui
author_facet Tan Rui
Eng, Yong Peng
format Final Year Project
author Eng, Yong Peng
author_sort Eng, Yong Peng
title Inaudible echo-based indoor position recognition (part 2)
title_short Inaudible echo-based indoor position recognition (part 2)
title_full Inaudible echo-based indoor position recognition (part 2)
title_fullStr Inaudible echo-based indoor position recognition (part 2)
title_full_unstemmed Inaudible echo-based indoor position recognition (part 2)
title_sort inaudible echo-based indoor position recognition (part 2)
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/147999
https://doi.org/10.1145/3264945
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