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Abstract. Location-aware services can benefit from indoor location tracking. The widespread adoption of Wi-Fi as the network infrastructure creates the opportunity of deploying WiFi-based location services with no additional hardware costs. Additionally, the ability to let a mobile device determine its location in an indoor environment supports the creation of a new range of mobile control system applications. Main area of interest is in a model of a radio-frequency based system enhancement for locating and tracking users of our control system inside the buildings. The developed framework as it is described here joins the concepts of location and user tracking as an extension for a new control system. The experimental framework prototype uses a WiFi network infrastructure to let a mobile device determine its indoor position. User location is used for data pre-buffering and pushing information from server to user's PDA. All server data is saved as artifacts (together) with its position information in building.

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The surveillance application aims at improving the quality of technology via modelling human expert behaviour in the coking plant Mittal Steel Ostrava, the Czech Republic. Video data on several industrial processes are captured by means of a CCD camera and classified by using Latent Semantic Indexing (LSI) with the respect to etalons classified by an expert. We also investigate the possibility to combine LSI with color histogram analysis, using experience from our prior research on web image classification. partial symmetric eigenproblem, very large systems of linear equations, iterative solvers