The information-preserving sampling properties of compressive sensing have found a number of successful applications, such as sensor scheduling, localisation and tracking to deal with the resource constraints of the embedded systems. In this paper, we investigate an approach to improve the performance of compressive sensing applications through a novel strategy for optimising the projection matrix. We formulate the projection matrix optimisation problem and apply greedy algorithm to solve the optimisation problem efficiently. We evaluate the proposed approach by an emerging background subtraction method designed specifically for the embedded systems and show the proposed approach outperforms existing approaches significantly with little overhead.