The increase in autonomy of ambient intelligence devices has led to the evolution of Internet of Things (IoT) towards the notion of Edge Computing and is driving Wireless Sensor Networks (WSN) (considered as the Low End Devices of IoT) towards total energy autonomy by recovering ambient energy. While the majority of current Machine Learning applications are still centralized in Clouds, we could take advantage of those frugal developments to propose systems that take into account their hardware and energy limitations for collaborative and adaptive distributed learning.