In this paper, we address the automated calibration of the pose of distributed laser range finders in smart environments, which are spaces with multiple embedded and networked sensors and actuators. This method is based on object tracking in overlapping sensing regions: the positions of same tracked objects in each sensor's coordinate system are used to calculate relative position and orientation of the sensors. We focus on extension of this mobile-assisted approach in order to utilize general moving objects such as humans and not limited to mobile robots. In case that mobile robots are used as calibration objects, the model of the mobile robots can be used to determine which mobile robots are being tracked. However, if the general moving object is utilized, we have to judge whether two tracked objects in different sensors are same object or not. So estimation error is utilized for the decision on the corresponding object. Experimental results shows that this method can find the correct correspondence and achieve almost the same result as manual calibration case.