E3DA has an open call for 1 PhD position at the IECS doctoral school at UNITN (Deadline Mon 16 May 2022 16:00).
This is it:
B9 – TinyAI for energy-efficient smart sensing in IoT (FBK)
Machine learning and deep neural networks are extensively and successfully used to process multimodal data (e.g., audio, video, environmental data) on powerful computers. At the same time, several challenges still need to be solved to bring AI on low consumption devices (e.g., end nodes in an IoT) with limited resources. Recently TinyML approaches are emerging to distribute the intelligence at the far edge in the edge-to-cloud continuum. Exciting research scenarios emerge, spanning from novel, innovative hardware for always-on and event-based sensing to tiny deep learning solutions for inference on resource-constrained platforms based on distillation, quantization, or neural architecture search. The complexity grows if we want to move learning to the edge. Motivated by these scenarios, the research aims to (i) define novel hardware/software approaches to optimize AI at the very edge on energy-efficient embedded devices, in particular for audio processing and/or computer vision; (ii) to explore the potential of distributing and fuse the intelligence in heterogeneous nodes of an IoT (iii) to demonstrate the advantages of the investigated approaches in real-world application scenarios, such as those of smart cities.