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The resource-constraints in the sensor networks make reliable data communication a challenging task. Particularly, the limited availability of battery and computing power necessitates designing computationally efficient means for providing data compression and protection against data loss. In this paper, we propose to integrate the emerging framework of compressive sensing (CS) with real expander codes (RECs), coined as CS-REC, for robust data transmission. CS works as a computationally inexpensive data compression scheme, while RECs act as an elegant application layer erasure coding scheme. The benefits provided by RECs are twofold: one, RECs require only few addition-subtraction operations over real numbers for encoding and decoding; two, they provide graceful degradation in recovery performance with increase in the number of erasures. Through elaborate simulations, we show that CS-REC can achieve the recovery performance close to the case where there is no data loss. Further, again via simulations, we demonstrate the usefulness of CS-REC for reliably transmitting image data in multimedia sensor networks.