Semantic Segmentation is a computer vision task that consists in assigning a label to every pixel in an input image. There are many applications for Semantic Segmentation such as scene understanding in autonomous driving or robot vision, land cover classification of satellite images, segmentation of medical images, etc. Semantic Segmentation models are often very complex and require powerful hardware. This clashes with their usage in a resource-constrained environment such as edge devices in an IoT network. For this reason, the standard approach when deploying these models in an IoT application is to offload both training and inference to a remote server.