During the last years, research on data processing in wireless environments has increased due to the emergence of mobile devices that are able to obtain real environmental sensory information (e.g., smartphones). Testing the different approaches in a real environment is not always possible due to high costs of deployment of hardware and users in many cases. However, the real world complexity can be simplified according to our needs as information systems always deal with simplified abstractions of real objects. For example, a system considering the location of a real car could simplify it as a certain entity with the same movement path. This can be achieved by using software simulations, which obtain approximated results reducing the costs. Nevertheless, it is difficult to develop an accurate real-world model to simulate the environmental conditions (e.g. uneven tracks, dynamic wireless network coverage, etc.). We introduce in this paper a hybrid simulation platform that is able to recreate real-world scenarios more accurately than software simulations. For that, it uses small affordable robots equipped with sensors in controlled real environments as counterparts of real moving objects and the scenario where they are involved. This enables testing the system considering real communication delays, real sensor readings, etc., instead of having to simulate such events. Finally, we present the experimental evaluation of the system using LEGO Mindstorms robots to simulate a real rowing race at the San Sebastian bay.