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This experiment presents the indoor localization system using the K-NN and D star algorithm applied to WiFi received signal strength. The experiment was conducted based on the building that is a one-floor plan and separated into 76 points, each point has a distance of about 1.2 meters. The data has been collected for 8,360 records and divided to form a training set and testing set for K-NN modeling. The result of the model, when K=1, is very delightful for further process. D star algorithm is the consequent step that results from K-NN identifying the current location and setting it as the starting point. The map also approximates generated to present the obstacle at four corners of the building. D star algorithm generates the optimal path by avoiding the obstacle and reach the target point as set before.
Although the proposed localization system provides a satisfying performance, other specific environments should be concentrated, for instance, the size of the object or vehicles that would like to implement this localization system. Developers should pay attention to the sophisticated detail of map generation for the K-NN and D*algorithm, which should correspond to each other.
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IEEE/ICACT20210203 Slide.24
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