WiFi-based indoor localization

• Main Author: Wong, Shi Heng
• Other Authors: Sinno Jialin Pan
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
• Online Access: https://hdl.handle.net/10356/156599
• Institution: Nanyang Technological University

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.