Indoor positioning systems are demanded at more and more places all over the world because positioning would be also required where satellite positioning (GPS) is not available. These areas are for example a workplace where employees can tracked, or a warehouse, where we can find the shortest route for the truck, thereby speeding up the work, or a parking garage, where drivers can easily navigate to the free parking places. In indoor environment a separate system must be installed to proved positioning and navigation services. In order to fulfill the requirements of the positioning systems at least three APs’ (access point) signal must be received, because the positioning algorithm can calculate the position from at least three different AP signals.
My goal is to develop a program, which can find the optimum with the minimum number of Aps for the indoor positioning system. The task can be traced back to the graph theory problem, known as the longest journey NP-hard problem. My work method uses the "simulated annealing" algorithm, which tries to find the near optimal AP structure of an indoor positioning system. This method helps to determinate the structure, where the necessary condition for the positioning algorithm is achievable with the minimum number of APs. The developed software reads the map from an image file, while the other parameters can be set by the user. Using the appropriate settings it is possible to operate the proposed method, for example WLAN, Bluetooth, UWB or any other access technology. The program during the initialization sets an AP in each grid point and then the algorithm reduces the number of APs, so looking for the best structure.
The program will help to plan the Allee shopping center’s parking system and give an estimation for the required number of APs, to help the developers work.