Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156599
Title: WiFi-based indoor localization
Authors: Wong, Shi Heng
Keywords: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Wong, S. H. (2022). WiFi-based indoor localization. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156599
Project: SCSE21-040
Abstract: In recent years, the demands for a better system that enables indoor localization have risen exponentially due to the increased pervasiveness of location-based services in various applications within our daily lives. While existing positioning technology such as the Global Positioning System (GPS) works sufficiently well in outdoor environments, the absence of GPS signals in indoor environments meant that it is not a feasible solution. Hence, this has pushed the interest of creating new and more robust indoor positioning systems (IPS) to greater heights. With that in mind, this study aims to provide a comparison in the performance of several IPS implementations through the use of Wi-Fi technology as well as advanced machine learning techniques. Through our experiments, we show that developing Wi-Fi-based indoor localization systems using machine learning is a viable and high-performing method.
URI: https://hdl.handle.net/10356/156599
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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