As the year comes to a close, we look back at the 3rd AIoTwin Summer School, held in June in conjunction with the SpliTech 2025 Conference. The summer school brought together PhD students, researchers, and industry professionals to explore key challenges and advances in Artificial Intelligence of Things (AIoT), edge intelligence, and distributed AI systems.
The programme featured a strong lineup of keynote lectures covering trustworthy decentralized infrastructures using blockchain technologies, human–robot interaction, and artificial intelligence–driven next-generation 6G networks.
In addition, a series of in-depth tutorials addressed current research and practical challenges, including machine learning under data distribution shifts, neural network compression for resource-constrained devices, time-series forecasting methods, edge load-balancing strategies for multi-camera object tracking in urban traffic scenarios, and decentralized training of graph neural networks for vehicle speed prediction.
Hands-on workshops showcased two open-source solutions developed within the AIoTwin ecosystem: the AIoTwin middleware for orchestrating hierarchical federated learning across large numbers of clients, and the SmartEdge toolchain for developing collaborative applications over dynamic, semantically described edge networks.
The summer school also included a dedicated thematic session at the SpliTech 2025 Conference on Artificial Intelligence of Things and Edge Intelligence. Topics ranged from AIoT architectures and edge AI algorithms to real-time data processing, continual learning, security, privacy, energy efficiency, and communication protocols. Participants additionally had the opportunity to attend broader conference sessions, fostering networking and knowledge exchange across academia and industry.
This video highlights the key moments, discussions, and collaborations that defined the 3rd AIoTwin Summer School and contributed to its success.