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A sensor selection method for distributed real-time sensing is proposed where the effect of communication delays is taken into account. First, a multi-sensor fusion algorithm that allows communication delays is proposed. This method takes advantage of the information form of Kalman filtering in order to maintain scalability with the number of sensors. Based on this algorithm, an algorithm is developed that calculates mutual information between an observation and the state to be estimated, which provides a criterion for sensor selection. Simulated results of a target-tracking task show its effectiveness.