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This paper presents the design of a novel architecture called CARE (Content-Aware Redundancy Elimination) that enables maximizing the informational value that challenged networks offer their users. We focus on emerging applications for situational awareness in disaster affected regions. Motivated by advances in computer vision algorithms, we propose to incorporate image similarity detection algorithms in the forwarding path of these networks. The purpose is to handle the large generation of redundant content. We outline the many issues involved in such a vision. With a Delay-Tolerant Network (DTN) setup, our simulations demonstrate that CARE can substantially boost the number of unique messages that escape the disaster zone, and it can also deliver them faster. These benefits are achieved despite the energy overhead needed by the similarity detectors.