Van Roy, PeterIsenguerre, NicolasNicolasIsenguerre2025-05-142025-05-142025-05-142024https://hdl.handle.net/2078.2/37490In today's world, applications based on the Internet-of-Things (IoT) are becoming more and more important. However, not all IoT devices are able to process the data they collect. This can become problematic in the context of real-time applications, as the latency introduced by the usage of the cloud for data processing can be unacceptable. This is limiting the potential that IoT devices could have in some fields, like in domotics or home automation applications where the real-time requirement is of the utmost importance. To solve this latency problem, IoT devices with more powerful embedded systems rely more and more on edge computing. In this context, the prototype of a moving robot using the GRiSP2 board for IoT and edge computing has been developed, as well as a dedicated Erlang/OTP application, named movement_detection. The robot is remotely controlled using dedicated gestures, which are detected by the accelerometer of an Inertial-Measurement-Unit plugged on a second GRiSP2 board. A library of gestures has been created for this application and the resulting robot behaviour for each gesture allows the user to move the prototype around as he wishes. Furthermore, many safety measures have been added to this prototype, as this application, based on "off-the-shelf" and cheap components, intends to show the potential of the GRiSP2 board in the context of domotics and Human-Robot interactions. In the first chapters of this thesis, the whole application, from the prototype to the software behind it, is fully described. Moreover, the performance of the system is detailed in the penultimate chapter, which also covers the current limitations the application faces. By going over the full process of thought, this thesis intends to inspire future generations of GRiSP2 users to improve the current system, as this application already shows promising results. Ideas for improvement and future works can be found in the final chapter of this work.HeraGRiSP2IoTRobotApplicationGesture recognitionRemote controlControlling everyday life objects using the Hera platform on GRiSP2.0: The movement_detection applicationtext::thesis::master thesisthesis:46003