The trajectory optimization problem for observation of distributed parameter systems, where wireless sensors are mounted on mobile robots, is considered. In this case the cost function is constructed based on the Fischer information matrix. The problem is formulated as an optimal control problem. The optimal sensor selection problem is considered. In this case the positions of the sensors are fixed. Thanks to the Fischer information matrix it is proved the observation based on a small number of sensors could be as precise as required of the observability on the whole network. A convex optimal sensor selection framework to select the proper sensors for generic parameter identification problems is proposed. The optimal beacon placement problem, about the balance between the positioning error and between placements, is discussed. Since the positioning errors of many localization systems are affected by the placement of the beacon nodes, it is desirable to place the beacons properly, so that the maximum positioning error is minimized. To solve the problem, a semi-infinite programming problem where the cost function is again based on the Fischer information matrix is formulated.