For the last 20 years, wireless videocapsule technology has triggered a lot of interest in the gastroenterologist community for the non-invasive early detection of various gastrointestinal pathologies (ulcers, Chrones disease, polyp detection, etc.). Nevertheless, in most of the European countries videocapsules are not yet considered as a systematic valid alternative to classic endoscopies and colonoscopies. Main reasons are in the existing technological limitations of videocapsules that are of two kinds: (i) A limited battery life-time (8 hours usually ensured by the manufacturer) that does not allow a complete imaging of the gastro intestinal tract, and (ii) the limited performance of the device in terms of detection rate of particular structures like polyps for instance which degenerations are at the origin of colorectal cancer. To overpass these limitations, main idea of our work is to develop a generation of smart videocapsules that takes advantage of the constant progress in electronics and most precisely in embedded signal processing tasks. In this Chapter, we give first a detailed overview of the most recent state-of-the-art related to videocapsules from the technological perspective in order to clearly positioned our work among the existing products and on going projects. In a second time, we propose a synthetic recall of the Cyclope project in the framework of which we are studying different strategies to improve the performance of current videocapsules in the particular context of the early diagnosis of colorectal cancer (polyp detection). We then propose a particular focus on the design optimization of the proposed algorithms from an electronic perspective. Most precisely, we give concrete elements and quantitative estimation (time processing, embedding performance, etc.) to show that embedding of the signal processing IP inside the videocapsule is feasible considering the most recent FPGA-platform performance, and that such an integration can bring a positive balance in terms of energy consumption by drastically reducing the amount of transmitted data.