A robust room-level localization method based on transition probability for indoor environments

Several scene analysis methods [1, 2] such as location fingerprinting have been proposed to execute room-level localization with high accuracy. However, these methods estimate locations wrongly when received signal strength (RSS) observed at a target user´s current position is similar to RSS in another place. By utilizing the heuristic of passing through a passable boundary point (for example, an entrance door) when moving between rooms, we introduce a technique for evaluating the distance between the current position of the target user and the boundary point by comparing RSS around the boundary point with RSS at the user in order to reduce the number of erroneous judgments. Experiments conducted in office environments confirmed that our proposed technique achieved an accuracy rate of 97.1% in localizing the target user.