Author : Yuan Yang (Ph. D. in civil engineering)
Publisher :
ISBN 13 :
Total Pages : 130 pages
Book Rating : 4.:/5 (131 download)
Book Synopsis Indoor Positioning System for Smart Devices by : Yuan Yang (Ph. D. in civil engineering)
Download or read book Indoor Positioning System for Smart Devices written by Yuan Yang (Ph. D. in civil engineering) and published by . This book was released on 2021 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the proliferation of personal smart devices in the last decade, mobile applications of indoor location-based services (ILBS) have been widely used in public buildings, such as hospitals, malls, school campuses and museums for patient monitoring, security management, asset tracking and indoor navigation, etc. As the core component of ILBS, indoor positioning systems (IPS) have gained increased attention. Since global navigation satellite systems (GNSS) are generally denied in indoor environments, as an alternative solution, many Radio Frequency (RF) based approaches of IPS have been proposed. However, these solutions either need to work in a controlled environment with customized RF infrastructure or could only offer low accuracy localization at the meter level. This work focuses on developing an innovative framework of IPS which is able to perform in any indoor environment without extra infrastructure and offers a robust and accurate localization estimation for smart device users. To achieve this goal, this work initially introduces a mean peak method that is subsequently combined with classification-based Wi-Fi fingerprint positioning (WF) techniques to deal with the challenges of positioning in a weak RSS environment. As the next step, the database updating problem for WF, including an innovative Bayes-inference-based sensor fusion framework which integrates WF and visual fingerprint positioning (VF) is addressed. The method provides both a location estimation and a heading direction estimation. In order to further improve the accuracy of the localization, a state-of-the-art visual localization algorithm, InLoc, is introduced in combination with WF for constructing a new IPS. Additionally, with the help of WF, the computational cost of InLoc is reduced compared to the original one. Moreover, to improve the robustness of the system, a particle filter and map updating function are introduced to optimize localization results and address the RSS variance problem. In summary, the proposed methodologies of this work define a framework for constructing an innovative IPS, a new path to build indoor positioning systems which are robust, easy to use and easy to deploy.