“Toward Ambient Intelligence: Osmotic Meta-Learning at the Intersection of IoT, Edge, and AI”
Abstract
As Internet of Things (IoT) devices continue to permeate our environments, they generate immense streams of real-world data that have the potential to transform how we deliver critical services—from healthcare and agriculture to transportation, smart grids, and disaster response. At the same time, advances in Artificial Intelligence, particularly Distributed Learning and Deep Learning, are unlocking new possibilities in areas like medical diagnostics, urban intelligence, and predictive analytics by learning from these rich, heterogeneous datasets.
However, a fundamental barrier persists: most deep learning models demand massive computational resources and centralized access to data—requirements typically fulfilled by cloud data centres. This centralized model often introduces latency, bandwidth constraints, and privacy challenges that are incompatible with real-time, context-aware decision-making at the edge.
In response, emerging paradigms like Osmotic Computing propose a more dynamic and adaptive distribution of intelligence—allowing computation to seamlessly flow between cloud, edge, and mobile edge environments. Yet, current approaches fall short in describing how to effectively orchestrate and scale distributed deep learning models across this complex continuum.
This keynote presents a vision for Osmotic Meta-Learning—a new class of resource- and data-aware learning algorithms designed to operate across globally distributed, heterogeneous environments. We will explore the following:
- The foundational concepts behind Osmotic Computing and its relevance to the future of ambient intelligence.
- Key research and programming challenges in building and coordinating distributed learning workflows that adapt to resource variability and data locality.
- A novel approach for training distributed deep learning models on thousands of mid-scale IoT and edge devices worldwide—circumventing the need for traditional GPU-heavy cloud infrastructures.
- Initial results from our deployment on the UK’s largest IoT testbed—the Urban Observatory (https://newcastle.urbanobservatory.ac.uk/)—which offers a real-world validation environment for scalable, osmotic AI systems.
This talk envisions a shift from siloed AI systems to fluid, collaborative, and context-aware intelligence, capable of learning from—and acting upon—the edge of everything.
Speaker’s Biography
Professor Rajiv Ranjan is an Australian-British computer scientist, of Indian origin, known for his research in Distributed Systems (Cloud Computing, Big Data, and the Internet of Things). He is University Chair Professor for the Internet of Things research in the School of Computing of Newcastle University, United Kingdom. He is an internationally established scientist in the area of Distributed Systems (having published about 350 scientific papers). He is a fellow of IEEE (2024), Academia Europaea (2022) and the Asia-Pacific Artificial Intelligence Association (2023). He is also the Founding Director of the International Centre (UK-Australia) on the EV Security and National Edge Artificial Intelligence Hub, both funded by EPSRC. He has secured more than $68 Million AUD (£34 Million+ GBP) in the form of competitive research grants from both public and private agencies. He is an innovator with strong and sustained academic and industrial impact and a globally recognized R&D leader with a proven track record. He serves on the editorial boards of top quality international journals including IEEE Transactions on Computers (2014-2016), IEEE Transactions on Cloud Computing, ACM Transactions on the Internet of Things, The Computer (Oxford University), and The Computing (Springer) and Future Generation Computer Systems. He led the Blue Skies section (department, 2014-2019) of IEEE Cloud Computing, where his principal role was to identify and write about the most important, cutting-edge research issues at the intersection of multiple, inter-dependent research disciplines within distributed systems research area including Internet of Things, Big Data Analytics, Cloud Computing, and Edge Computing. He is one of the highly cited authors in computer science and software engineering worldwide (h-index=83+, g-index=290+, and 34000+ google scholar citations, h-index=65+ and 19000+ Scopus citations, and h-index=50+ and 12000+ Web of Science citations).
Is my Ubiquitous Computing your IoT?
Abstract
35 years ago Mark Weiser has published his seminal paper on “the Computer of the 21st century” founding the research in Ubiquitous Computing. I want to take you on a journey revisiting some research in Ubiquitous Computing and adjacent fields during the past decades and relate this to IoT.
Speaker’s Biography
Christian Becker is a full professor for Computer Science at the University of Stuttgart since April 2022. Prior to that he was a full professor for Information Systems at the University of Mannheim from 2006 till 2022.
Christian studied Computer Science at the Universities of Karlsruhe and Kaiserslautern where he graduated in 1996. He received his PhD from the University of Frankfurt in 2001. In 2001 he joined the distributed systems group at the University of Stuttgart as Post Doc. In 2004 he received the venia legendi (Habilitation) for Computer Science (Informatik). Christian’s research interests are Distributed Systems and Context-Aware Computing. He is specifically interested in architectures for adaptive systems and their application to distributed systems.
Christian has published more than 200 technical papers. He is a member of the IEEE Pervasive Computing and Communication Conference (PerCom) steering committee. Christian is active in the community, e.g., he was general chair of IEEE PerCom in 2010, TPC chair in 2016. He was/is general chair of IEEE Mobile Data Management in 2007 and 2023 and contributed to many other scientific venues.
Closing Keynote
Distributed Intelligence towards Agentic AI.
The recent revolution in LLMs has brought us closer to new AI challenging dimensions. How has this been achieved by leveraging the Cloud and Big Data? Moreover, starting from the Cloud and moving towards the Edge, Distributed Intelligence, like Federated Learning, is representing one of the new outcomes in this domain, and the current trend of Agentic AI is speeding up thanks to it. Let’s take a look.
BIO
Massimo Villari is Full Professor in Computer Science at University of Messina (Italy). He is actively working as IT Security and Distributed Systems Analyst in Cloud and Edge Computing, virtualization and Storage, Federated Learning and one of the creators of Osmotic Computing Paradigm. For the EU Projects “RESERVOIR” he leaded the IT security activities of the whole project. For the EU Project “VISION-CLOUD” and “H2020-BEACON”, he covered the role of architectural designer for UniME. He was Scientific ICT Responsible in the EU Project frontierCities, the Accelerator of FIWARE on Smart Cities – Smart Mobility. He is strongly involved in EU Innovation initiatives, and also, he covers the role of EU external expert. Currently, he is Scientific ICT Responsible for UniME of “TEMA” and “NEUROKIT-2E” Horizon Europe Projects. He is co-author of more of 250 scientific publications and patents in Cloud Computing (Cloud Federation), Distributed Systems, Wireless Network, Network Security, Cloud Security and Cloud, Edge and IoTs, and recently in Osmotic Computing and AI. He was General Chair of ESOCC 2015 and IEEE-ISCC 2016. In 2014 he was recognized by an independent assessment (IEEE Cloud Computing Transaction, Issue April 2014) as one of World-Wide active scientific researchers, top 27 classification, in Cloud Computing Area. He was General Chair of IEEE-ICFEC 2019 and General Co-Chair in IEEE-CCGRID2022. He was also General Chair of IEEE ISCC2022 and IEEE ISCC2024. He is in the Stanford World’s Top 2% Scientists list of the Stanford University in Computer Science. He is a Co-Founder of UniME Spin-Off Alma Digit S.R.L since 2017. He was Rector delegate on ICT for whole University of Messina and Academic and Consultant for the Messina Municipality in the Area of Smart Cities. Currently he is the Head of Computer Science and Data Science Schools.