چكيده به لاتين
localization device or person inside the building is a subject that has attracted many researchers in recent years. GPS technology, which often used for localization, can not effectively be used to detect posiotions inside buildings due to the loss of signal propagation. Among the methods of indoor localization, wireless fingerprint methods have been very important recently, using the power of the received signal (RSS), because they are more effective and less costly. Among the WLAN positioning methods, WLAN fingerprint positioning has attracted a lot of attention recently due to promising results. a way that can be considered in user localization in fingerprint algorithms is classification to limit the problem space to a subset of total space. The most common of today's solutions is the use of a file containing RSSs collected from different APs that are visible in different parts of the environment indoor the building. This research, also known as fingerprinting localization, specifies that at each specific test point, what AP signals and to what extent can be obtained. In this way, when evaluating and localization, it is sufficient to use the various strategies, such as classification and prediction, to indoor localization. This research focuses on indoor localization by reducing the number of APs. By reviewing some associative rules and algorithms repeatedly and using the CPAR algorithm, the number of APs used in positioning has been reduced. This is accomplished by removing APs that are rarely or too frequent. According to the results, it is proven that the cost and time of localization will be reduced and the positioning will be carried out with acceptable accuracy.
