93 citations · 319 across the 30 of their papers we have counts for
33 papers
QoS-Aware Federated Learning for Multimodal In-Cabin Interaction in Smart Vehicles
Baran Can Gül, Mert Nakıp, Nasser Jazdi +1
Modern smart vehicles leverage multimodal sensors, ranging from high-bandwidth vision systems to low-rate physiological monitors, to provide personalized in-cabin services. However…
SecureDrive-FL: Joint Differential Privacy and Gradient-Aware Selective Homomorphic Encryption for Federated Driver Monitoring
Baran Can Gül, Hanuma Siddhartha Tunuguntla, Anjana Arvind Naik +3
Federated Learning (FL) enables privacy-aware distributed training, yet gradient updates remain exploitable: Man-in-the-Middle (MitM) interception exposes updates in transit, while…
LLM Agents Perform Controlled Experiments Using Simulation Models
Yuchen Xia, Michael Weyrich, Nasser Jazdi +6
Large language models (LLMs) have shown strong capabilities in reasoning, planning, and tool use, but many scientific and engineering tasks require more than plausible text and cod…
Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles
Matthias Weiß, Athreya Hosahalli Prakash, Maurice Artelt +3
Connected vehicles are autonomous cyber-physical systems whose behavior must be continuously monitored during operation to detect deviations from normal operation before they propa…
Evaluating Hardware Abstraction Layer Concepts for Software Defined Vehicles: Insights into Applicability and Effectiveness
Akshay Narla, Johannes Stümpfle, Souvik Saha +2
The emergence of Software-Defined Vehicles represents a fundamental shift in automotive design, prioritizing software-centric architectures over traditional hardware-driven models.…
SDVDiag: Multimodal Causal Discovery for Online Diagnosis in Software-defined Vehicles
Matthias Weiß, Athreya Hosahalli Prakash, Falk Dettinger +2
The transition toward software-defined vehicles concentrates an increasing share of vehicle functionality into distributed software services, where failures propagate through servi…
Towards Intelligent Computation Offloading in Dynamic Vehicular Networks: A Scalable Multilayer Pipeline
Falk Dettinger, Matthias Weiß, Baran Can Gül +3
Software Defined Vehicles face an increasing computational gap as advanced algorithms and frequent software updates demand more processing power while onboard hardware remains stat…
SDVDiag: Using Context-Aware Causality Mining for the Diagnosis of Connected Vehicle Functions
Matthias Weiß, Falk Dettinger, Elias Detrois +2
Real-world implementations of connected vehicle functions are spreading steadily, yet operating these functions reliably remains challenging due to their distributed nature and the…
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…
Communication Architecture for Autonomous Power-to-X Platforms: Enhancing Inspection and Operation With Legged Robots and 5G
Peter Frank, Falk Dettinger, Daniel Dittler +4
Inspection and maintenance of offshore platforms are associated with high costs, primarily due to the significant personnel requirements and challenging operational conditions. Thi…
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…
Efficient Creation of Behavior Models with Variable Modeling Depths Used in Digital Twins
Valentin Stegmaier, Walter Schaaf, Nasser Jazdi +1
Behavior models form an integral component of Digital Twins. The specific characteristics of these models may vary depending on the use case. One of these key characteristics is th…
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…
Incorporating Large Language Models into Production Systems for Enhanced Task Automation and Flexibility
Yuchen Xia, Jize Zhang, Nasser Jazdi +1
This paper introduces a novel approach to integrating large language model (LLM) agents into automated production systems, aimed at enhancing task automation and flexibility. We or…
Tackling Erosion in Variant-Rich Software Systems: Challenges and Approaches
Johannes Stümpfle, Nasser Jazdi, Michael Weyrich
Software product lines (SPL) have emerged as a pivotal paradigm in software engineering, enabling the efficient development of variant-rich software systems. Consistently updating…
Knowledge Graphs in the Digital Twin: A Systematic Literature Review About the Combination of Semantic Technologies and Simulation in Industrial Automation
Franz Georg Listl, Daniel Dittler, Gary Hildebrandt +3
The ongoing digitization of the industrial sector has reached a pivotal juncture with the emergence of Digital Twins, offering a digital representation of physical assets and proce…
Illustrating the benefits of efficient creation and adaption of behavior models in intelligent Digital Twins over the machine life cycle
Daniel Dittler, Valentin Stegmaier, Nasser Jazdi +1
The concept of the Digital Twin, which in the context of this paper is the virtual representation of a production system or its components, can be used as a "digital playground" to…
LLM experiments with simulation: Large Language Model Multi-Agent System for Simulation Model Parametrization in Digital Twins
Yuchen Xia, Daniel Dittler, Nasser Jazdi +2
This paper presents a novel design of a multi-agent system framework that applies large language models (LLMs) to automate the parametrization of simulation models in digital twins…
Simulating Cloud Environments of Connected Vehicles for Anomaly Detection
M. Weiß, J. Stümpfle, F. Dettinger +2
The emergence of connected vehicles is driven by increasing customer and regulatory demands. To meet these, more complex software applications, some of which require service-based…
Generation of Asset Administration Shell with Large Language Model Agents: Toward Semantic Interoperability in Digital Twins in the Context of Industry 4.0
Yuchen Xia, Zhewen Xiao, Nasser Jazdi +1
This research introduces a novel approach for achieving semantic interoperability in digital twins and assisting the creation of Asset Administration Shell (AAS) as digital twin mo…
Qualitative and quantitative evaluation of a methodology for the Digital Twin creation of brownfield production systems
Dominik Braun, Nasser Jazdi, Wolfgang Schloegl +1
The Digital Twin is a well-known concept of industry 4.0 and is the cyber part of a cyber-physical production system providing several benefits such as virtual commissioning or pre…
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…