24th International Conference on Embedded Wireless Systems and Networks

Featured Topic: Decentralized and privacy-aware intelligence in networks of resource-constrained heterogeneous devices.

Most current work on smart systems relies on AI and ML pipelines in which sensor nodes act primarily as data providers or as clients of centralised services. What happens when the intelligence moves into the network itself: when sensing, learning, inference and coordination are distributed across devices that differ widely in capability and that operate under tight budgets for energy, memory, bandwidth and heat? Decentralized and privacy-aware intelligence takes a different route: it emerges from decentralised interactions in the network itself, involving voting, consensus and local coordination, allowing data to stay with the contributor, as in federated systems and enabling levels of privacy that centralised architectures cannot offer.

Microcontroller-class sensor nodes, XR headsets and other wearables carried on the body, robotic and vehicular platforms, the edge and cloud resources that orchestrate them, and, at the far end of the spectrum, biocompatible nanodevices that sense and communicate inside living organisms. What these have in common is that the useful computation rarely fits on any single node, so the design question becomes which function runs where, and how the parts stay in agreement.

The obstacles are real. Nodes are heterogeneous, resources are tight, and coordination is hard without a central authority. More capable components at the edge, at the telco or in the cloud can help orchestrate local interactions, provided privacy requirements are not compromised in the process.

EWSN 2027 invites workshop, tutorial and panel proposals across this space, from embedded and time-resilient ML to thermal-aware system design to molecular and bio-nano communication, and the keynote programme will reflect this focus.