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Path and location tracking are one of the main interesting and fast growing applications in Mobile and Wireless Communications. The developments of such systems have interested many research, industrial and government bodies with solutions that range in scale and accuracy. The GPS system, Cell based tracking in cellular networks are just few examples. However such technologies have their limitations. GPS does not work inside buildings, cellular systems are not owned by organizations and only work with mobile phones and have high subscriptionfees.The prototype implemented in this paper illustrates a simple path and location tracking system within an organization based on its available infrastructure Wi-Fi network. By using signal strength and histories ofaccess points used by a mobile node we can provide an approximate determination of the location in the services area and also the moved path of the mobile node. In our work we use web services for location services to enable queries and manage the path and location of the mobile node. The system has shown impressive results that enable software developers to provide useful types of location based service applications for organizational tasks.

Search engine is the popular term for an information retrieval (IR) system. Typically, search engine can be based on full-text indexing. Changing the presentation from the text data to multimedia data types make an information retrieval process more complex such as a retrieval of image or sounds in large databases. This paper introduces the use of language and text independent speech as input queries in a large sound database by using Speaker identification algorithm. The method consists of 2 main processing first steps, we separate vocal and non-vocal identification after that vocal be used to speaker identification for audio query by speaker voice. For the speaker identification and audio query by process, we estimate the similarity of the example signal and the samples in the queried database by calculating the Euclidian distance between the Mel frequency cepstral coefficients (MFCC) and Energy spectrum of acoustic features. The simulations show that the good performance with a sustainable computational cost and obtained the average accuracy rate more than 90%.

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