الفهرس 
Overview of Wireless Indoor Localization TechnologiesOnly 14 pages are availabe for public view
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Abstract
The rapid evolving of Smartphone operating systems such as Android and iPhone Operating System (iOS) in the last few years has led to increase in the interest of developing many applications in many fields. Currently, due to the increasing demand for indoor localization services which are used to guide individuals to move around in many indoor places such as airports, museums, subway stations, exhibitions and conferences halls, and many other services, attention has been given to the development of many applications in this area using Smartphone operating systems.
Smartphone is considered to be the best platform used for developing indoor localization services because they included a high resources’ capability such as a fast processor, a large memory, and usually use multiple wireless technologies like Wireless Fidelity (Wi-Fi), Bluetooth, Radio Frequency Identification (RFID), and so on. As well as, the using of Smartphone for indoor localization services can save a lot in required devices for implementing these services.
Although Wireless Local Area Network (WLAN) is not designed for indoor localization determination, most of the recent researches started to use the existing WLAN infrastructure to determine indoor locations; this has been encouraged by the widespread of its use in public places and corporations and enables mobile phones to communicate with each other. Most of the indoor localization techniques used WLAN are based on mapping each location to the received signal strength received by mobile phone from each visible access point.
In WLAN localization system, the signal strength can be represented by two types of modeling, fingerprint modeling and propagation modeling., The distribution of the Received Signal Strength (RSS) cannot be described accurately by simple propagation models due to the interference of RF signals in indoor environments that lead to a complex spatial distribution of the RSS.
Hence, in recent years, most researches started focusing on using fingerprinting modeling in which the RSS map is constructed for indoor environments. So, fingerprinting modeling is used in this thesis. Location fingerprinting consists of two modes: offline mode which is known as a training mode and online mode which is known as a positioning mode.
In this thesis, WLAN indoor localization application based on a proposed RSS model and fingerprinting is developed on Android Smartphone. A proposed RSS model is formulated to be used in fingerprinting offline mode and online mode for detecting the location accurately. The range and the midrange methods are used in this model that gives a new mean and standard deviation as called in this thesis. Also, the frequency distribution patterns are calculated for the RSS signals and used in the RSS model. The application of this thesis is tested in City Center Mall in Nasr City, Cairo, Egypt, and the result of testing gives the location name correctly except some locations are not determined well. As well as, the distance between adjacent locations is adjusted to five meters instead of four meters which improves the accuracy of the proposed application and reduces the effect of the aliasing problem.
The comparison is done with other indoor localization research and with Ekahau system. The results of the comparison showed that the proposed model is better in some aspects than the comparative research and Ekahau system. The results of the comparison can be used by other researchers as a guide to improving the indoor localization system. As well as the using of Smartphone for indoor localization provides more possibilities as well as simplifies implementation and facilitates deployment. Further measurements and tests will be done in future work to address the problem that faced the developed Android application.