galileo 2

Mario Miosga and Daniel Scherz evaluating the light weighted design

Students at Ubiquitous Computing Lab are developing several prototypes when studying subjects in a Bachelor or Master degree. Quite often, the solution is composed of Hardware and Software. While the software can be placed on common application environments (like PCs or Smartphones), additional components, like for example sensors, need to be interfaced. Furthermore, the expected behavior of a sensor ranges from pure raw data capturing up to complex preprocessing with adequate algorithms before any data transfer takes place. The requirements to the platform are raising, while the time to study new platforms remain constant (at least during regular lecture exercises). In the past, most of these designs were placed on the widely used Arduino Uno prototyping platform. Recent developments have shown that several ideas had to be modified or even skipped because more processing power and communication flexibility is needed for innovative solutions. The Intel Galileo Gen 2 allows reusing the knowledge gained in the lab during prototyping in the past and it provides a new perspective to empower prototypes because Intel Galileo is Arduino-certified. The Intel board is hardware-, software-, and pin-compatible with a wide range of Arduino Uno R3 shields so that lab equipment can be further used.

Prof. Dr. Seepold and his team tutored many student exercises and research approaches during the last years. On the one hand side prototypes require more embedded power and space to host complex algorithms but on the other hand side, prototypes need to be available quickly. The one time investment in a simple platform like Arduino will pay off when transferring more sophisticated systems on a more powerful platform like Galileo. This platform is providing more space for program an data and more interfaces on board. The latter case is especially important when designing for mobile environments. 

Mario started to research on his Bachelor thesis entitled Map-Reduce Architecture on Intel Galileo.

 

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