8 papers
FedMultiEmo: Real-Time Emotion Recognition via Multimodal Federated Learning
Baran Can Gül, Suraksha Nadig, Stefanos Tziampazis +2
In-vehicle emotion recognition underpins adaptive driver-assistance systems and, ultimately, occupant safety. However, practical deployment is hindered by (i) modality fragility -…
Model-Based Control for Power-to-X Platforms: Knowledge Integration for Digital Twins
Daniel Dittler, Peter Frank, Gary Hildebrandt +3
Offshore Power-to-X platforms enable flexible conversion of renewable energy, but place high demands on adaptive process control due to volatile operating conditions. To face this…
A Concept for Autonomous Problem-Solving in Intralogistics Scenarios
Johannes Sigel, Daniel Dittler, Nasser Jazdi +1
Achieving greater autonomy in automation systems is crucial for handling unforeseen situations effectively. However, this remains challenging due to technological limitations and t…
Control Industrial Automation System with Large Language Model Agents
Yuchen Xia, Nasser Jazdi, Jize Zhang +2
Traditional industrial automation systems require specialized expertise to operate and complex reprogramming to adapt to new processes. Large language models offer the intelligence…
SyncFed: Time-Aware Federated Learning through Explicit Timestamping and Synchronization
Baran Can Gül, Stefanos Tziampazis, Nasser Jazdi +1
As Federated Learning (FL) expands to larger and more distributed environments, consistency in training is challenged by network-induced delays, clock unsynchronicity, and variabil…
A Modular System Architecture for an Offshore Off-grid Platform for Climate neutral Power-to-X Production in H2Mare
Pascal Häbig, Daniel Dittler, Maximilian Fey +5
Power-to-X (PtX) products constitute a promising solution component in the defossilisation of hard-to-abate sectors. Where direct electrification is not possible, they can find app…