The Structural Health Monitoring (SHM) problem for critical infrastructures using wireless sensor networks (WSN), has received considerable attention in the research community in recent years. Sensors placed in these infrastructures have two functions, sensing/coverage and communication. The thrust of this paper is on the coverage aspects of sensor networks. In the Point Coverage model, only a specified set of points in the deployment area have to be sensed. The goal of placement optimization is to find the smallest set of locations to deploy sensors, so that all the points of interest can be sensed. This problem often is solved by formulating it as a Set Cover problem. However, the Set Cover approach has a serious limitation on the accurate identification of the location where abnormality is sensed. In this paper, we present a technique to overcome this limitation by utilizing Identifying Code. We study two different scenarios, where the sensors and points of interest are located in one and two-dimensional spaces respectively. We provide a polynomial time optimal algorithm for the one-dimensional case and an Integer Linear Programming (ILP) based optimal solution for the two-dimensional case. We evaluate the efficacy of the ILP solution with varying network size (45 to 64655 nodes). The ILP produced an optimal solution for the largest instance with 64655 nodes and 155339 edges in only 180.45 seconds.