Twinning action for spreading excellence in Artificial Intelligence of Things

A new article titled “Handling Dynamics in HFL Pipelines: The Need for Adaptive Orchestration” , authored by Ana Petra Jukić , has been published as part of the ongoing AIoTwin project blog series . The article reflects work carried out during and following the author’s short-term exchange at Technische Universität Berlin , focused on advanced orchestration strategies for Hierarchical Federated Learning (HFL). The text discusses key challenges arising in dynamic environments, where HFL pipelines may become suboptimal due to node arrivals or departures, fluctuations in resource availability, or non-uniform data distributions. It outlines the importance of adaptive orchestration and provides an overview of the AIoTwin orchestration middleware , developed on Kubernetes, which monitors performance, resource usage, and cost metrics to support intelligent and timely reconfiguration of HFL pipelines. The article also presents the Reconfiguration Validation Algorithm (RVA) , a method used to assess whether newly applied configurations offer real improvements without exceeding defined budget constraints. The full article is available here .

The AIoTwin project has released a new article in its ongoing blog series, focusing on Hierarchical Federated Learning (HFL) - an emerging approach designed to enhance the scalability and efficiency of distributed learning across Cloud-Edge-IoT (CEI) environments. While traditional Federated Learning (FL) enables collaborative model training without sharing raw data, it often faces limitations in scalability and communication efficiency. HFL addresses these challenges by introducing an intermediate layer of edge aggregators , creating a robust, multi-tier learning architecture that supports more decentralized and resilient AI applications. The blog post, authored by Katarina Vuknić following her research exchange at the Distributed Systems Group (DSG) , TU Wien , as part of the AIoTwin project , explores several key aspects of HFL: Communication Efficiency: How HFL significantly reduces uplink communication costs compared to flat FL architectures. Trade-offs: Analyzing challenges such as convergence delay, gradient variance, and model divergence in multi-level aggregation setups. Real-World Impact: Demonstrating the use of HFL in applications like smart farming and intelligent traffic management systems. The AIoTwin Solution: Presenting the open-source Extension of the Flower Framework for HFL , a Python-based component that enables scalable client, local, and global aggregation across the CEI continuum. The AIoTwin HFL solution offers a flexible, modular implementation of federated learning services designed to support distributed AI orchestration from the edge to the cloud. It represents a key step forward in advancing open, adaptive, and privacy-preserving machine learning for next-generation intelligent systems. The full article is available here .

A new blog post has been published focusing on the Artificial Intelligence of Things (AIoT) and the outcomes of the AIoTwin project. AIoT is revolutionizing the way humans and systems interact with the physical world by embedding intelligence directly into devices — from city cameras to industrial sensors. By integrating AI across Cloud-Edge-IoT (CEI) environments, AIoT enables systems that can learn, reason, and make autonomous decisions in real time. However, this transition from cloud-only or edge-only AI to a full computing continuum introduces new challenges, including determining where AI models should run — in the cloud, at the edge, or across both. The first blog post, authored by Ivana Podnar Zarko , explores several key aspects: Real-time traffic monitoring as a practical AIoT use case Cloud vs. edge-based AI: accuracy, latency, network load, and privacy trade-offs Why hybrid deployments across the computing continuum are the future Key technical challenges: optimal service placement, dynamic routing, federated learning, fault tolerance, and model updates As a solution, the AIoTwin Orchestration Middleware has been introduced. Developed by researchers at IoTLab@FER (Ivan Čilić, Ana Petra Jukić, Katarina Vuknić) in collaboration with researchers from Technische Universität Wien (Pantelis Frangoudis, Anna Lackinger, Ilir Murturi, Alireza Furutanpey, Schahram Dustdar), the middleware delivers a suite of open-source tools — including the fl-orchestrator , Flower extension for HFL , and QEdgeProxy . These tools form the foundation for scalable, adaptive, and intelligent AIoT deployments spanning from the edge to the cloud. The full blog post is available here , with additional technical articles from consortium members to follow.

Berlin, 24.6.2025.  The AIoTwin consortium is on the road again shortly after the 3rd Summer School. Fraunhofer FOKUS , one of Germany’s leading institutes for applied research in ICT, organized the Business Development & Innovation Transfer Workshop to foster the commercialization of Artificial Intelligence of Things (AIoT) innovations developed within the AIoTwin project . A full-day focused workshop placed special emphasis on exploring the business potential of the consortium’s AIoT middleware, offering insights into technology transfer, market readiness, and commercialization strategies. The one-day workshop featured a series of targeted presentations and collaborative challenges, fostering discussion and practical reflection on business development and innovation transfer strategies. Topics included: Lean Canvas for structuring and validating AIoT business ideas Technology Readiness Level (TRL), Market Readiness (MRL), and Product Readiness (PRL) assessments Business model design and approaches for real-world implementation Participants gained a deeper understanding of how to translate AIoT research into viable products and services. They left with validated business concepts, clearer market positioning, and concrete next steps for implementation. For more pictures from the workshop, open the detailed news content.

The detailed program for the third and final AIoTwin Summer School has been released. Set to take place from June 16 to June 18, 2025 , in Split, Croatia , the event will focus on the intersection of Internet of Things (IoT) and Artificial Intelligence (AI) . The Summer School will be co-located with the 10th SpliTech Conference , offering attendees the unique opportunity to participate in both events. This collaboration will provide enhanced networking and learning opportunities, making it a must-attend for those interested in the latest developments in IoT and AI. The detailed programme is available  here . More information about the summer school is available here .

The AIoTwin consortium met in Vienna from May 6–9, 2025 for the plenary meeting, where they reviewed the project's progress and discussed the next steps. Alongside the plenary sessions, participants attended a talk, a tutorial, and a workshop, each aimed at enhancing their knowledge and supporting collaboration. The meeting kicked off with a dedicated PhD student roundtable , fostering dialogue and exchange among PhD candidates within the consortium. This session provided a platform for emerging researchers to discuss their work and engage with fellow researchers. On the second day, participants took part in an Innovation Management Workshop organized by TU Wien's Innovation Incubation Center (I2C) , with Alexandra Negoescu leading the session. The workshop concentrated on strategies for translating academic research into practical applications, offering valuable insights into innovation, entrepreneurship, and technology transfer. Later in the day, Prof. Schahram Dustdar delivered a talk on “ The Art and Science of Writing Publishable Research ”, offering guidance on navigating the paper publishing process. The day concluded with a tutorial on " Autonomous Orchestration of Computing Continuum Systems through Active Inference ", presented by Boris Sedlak (TUW) . The session provided practical knowledge, enhancing participants’ understanding of these emerging technologies. The final two days were dedicated to plenary sessions, during which consortium members presented updates on work packages, shared progress, and engaged in discussions. The consortium will be meeting soon again, in Split, Croatia, for the third and final AIoTwin Summer School , co-located with the SpliTech Conference. Find out how to participate here .   For more pictures from the plenary meeting, open the detailed news content.

As we prepare for the 3rd and final AIoTwin Summer School , we’re taking a moment to reflect on the incredible experience we had in Dubrovnik, Croatia , during our 2nd Summer School . The event took place at the  Centre for Advanced Academic Studies (CAAS)   of the  University of Zagreb , which offers a stunning view of Dubrovnik's Old Town's famous City Walls and Lovrijenac Fortress. The event was organized in  collaboration with the EU funded  SmartEdge  project . The summer school program included invited talks, technical tutorials, hands-on sessions with advanced hardware, poster sessions showcasing the latest research, and other insightful presentations and discussions. In addition, the program included a technical workshop on “ Edge AI meets Swarm Intelligence “, featuring insightful presentations and discussions on cutting-edge research. Take a look at the vibrant atmosphere from our 2nd Summer School — and don’t miss your chance to be part of the final edition in Split, Croatia , co-located with the  10th edition of the  SpliTech conference !    

We’re excited to announce the 3rd and final edition of the AIoTwin Summer School, organized under the Horizon Europe Twinning project AIoTwin, taking place from June 16 to 18, 2025, in the stunning and historic city of Split, Croatia. The summer school will feature a rich and engaging program, including invited talks from leading researchers, technical tutorials, hands-on sessions with advanced hardware, and interactive discussions on emerging trends and research challenges. 🔗 Co-located with the SpliTech 2025 Conference (June 16–20) The AIoTwin Summer School is co-located with the SpliTech 2025 Conference, taking place from June 16th to 20th in Split and on the nearby island of Brač (Bol). This co-location offers participants an exceptional opportunity to immerse themselves in a broader scientific and professional community, fostering interdisciplinary exchange and collaboration. As part of the SpliTech program, the AIoTwin project will host a special session dedicated to AIoT and Edge Intelligence, focusing on topics such as the design of edge AI architectures, real-time data processing, continual learning, privacy and energy-aware solutions, and communication challenges in real-world applications.  ℹ️ Information  Register here: form Registration deadline: May 16th, 2025 For more details on the event programme, registration, special session, and more, visit the 3rd Summer School page . Don't miss this opportunity to be part of a transformative learning experience that's shaping the future of AIoT and Edge AI!  

We're excited to share that Prof. Ivana Podnar Žarko, AIoTwin coordinator, presented the AIoTwin Orchestration Middleware at the STEADINESS workshop during HiPEAC 2025 in Barcelona (Jan 20-22, 2025)! 🚀 Her presentation, " Artificial Intelligence of Things (AIoT): Bringing Intelligence into the Physical World ," highlighted the critical need for adaptive and QoS-aware orchestration middleware in the evolving IoT-edge-cloud continuum. This middleware, now open-source on our GitHub repository https://github.com/aiotwin , is designed to manage both learning and inference pipelines. Prof. Podnar Žarko presented the requirements and architecture of our solution, which extends traditional orchestrators like Kubernetes with AIoT-specific capabilities. We're focused on optimizing resource utilization by considering both infrastructure-related QoS (latency, communication cost) and AI-related performance metrics (accuracy, loss). Key takeaways from the STEADINESS workshop emphasized the necessity for: scalable and adaptable engineering methodologies, especially in safety-critical sectors like automotive, aerospace, and industrial automation; modular and interoperable solutions leveraging RISC-V and AI for embedded systems to enhance resilience and performance. clear AI regulation guidelines that balance innovation with ethical and security considerations. For more information, check out the workshop's joint whitepaper: https://zenodo.org/records/14920027 .

Mislav Has participated in the fourth short-term staff exchange as part of the AIoTwin project, hosted by the Research Institutes of Sweden, RISE  from November 19 to December 18, 2024.  During this period, Mislav collaborated closely with researchers at RISE, exploring advanced techniques for deploying WebAssembly on constrained devices and addressing key challenges in balancing performance and resource efficiency. The exchange involved in-depth discussions, hands-on experimentation, and the initiation of joint research efforts in the field of IoT and energy-efficient computing. The outcomes of this collaboration will be disseminated through future publications, paving the way for ongoing partnerships and advancements in IoT technologies.  For those interested in a visual recap of this exchange, a YouTube video documenting highlights is available  here .