SS01 - AI-based Safe, Secure, and Sustainable (I)IoT

Special Session Organized by

Muhammad Taimoor Khan, University of Greenwich, UK, and Dimitrios Serpanos, ISI Athena, ECE, University of Patras, Greece, and Howard Shrobe, MIT CSAIL, USA, and Kunio Uchiyama, AI Chip Design Centre, Japan,

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Focus

Computing constitutes a fundamental component of the emerging initiatives like Society 5.0, Industry 5.0, Healthcare 5.0, and Agriculture 5.0 (aka X 5.0), which combine cyber and physical spaces (i.e., processes) and require control and monitoring techniques for their operation and management. In X 5.0, people, things, devices, and systems are connected in cyberspace and operate exploiting automated methods, including machine learning (ML) and artificial intelligence (AI). Such operation and management bring new value to industry and society in ways not previously possible. Typical cyber-physical systems (CPS) are based on (I)IoT (Industrial - Internet of Things) and (I)CPS (Industrial - Cyber Physical Systems) and have applications in all critical infrastructure domains with strict real-time requirements, such as healthcare, electric grid, transportation, to name a few. Intentional or accidental errors/failures/attacks to these systems have highly severe consequences. Therefore, novel design methodologies are required to ensure that design of real-time cyber-physical systems and applications in the emerging Society 5.0 are free of vulnerabilities, threats, and attacks. Since the physical part of CPS involves several processes, typically, it is challenging to ensure that the design is free from all known vulnerabilities. It is necessary to develop run-time monitoring and analysis techniques that can help to detect run-time incidents by observing the processes and their data. Furthermore, adequate modeling of CPS physical processes and corresponding cyber and physical attacks is fundamental to systematically model, analyze, and verify real-time security of CPS. Importantly, since AI and machine learning have demonstrated their success in many application areas, including cybersecurity, this special session focuses on investigating AI, machine learning, and formal methods-based techniques to develop safe, secure, privacy, and law-aware real-time cyber-physical systems, digital twins, and smart cities at all levels, from hardware components to applications.

Topics under this track include (but not limited to):
  • Design-time and run-time safety, security, privacy, and law in modern systems, e.g., X 5.0, Digital Twins, ICPS, and IIoT.
  • Data-driven (AI and Machine Learning or model)-based safety, security, privacy, and law in cyber-physical systems (CPS), networks, and communication
  • Prevention, detection, and mitigation techniques for real-time CPS (RT-CPS) applications against cyber, non-cyber, and cyber-non-cyber threats
  • Hardware design for safe, secure, privacy, and law-aware RT-CPS
  • Vulnerability analysis of RT-CPS applications
  • Attack modeling and performance analysis of RT-CPS
  • Formal methods (FM)-based safety and security of critical systems at design-time and run-time
  • Safety, security, and privacy of citizens in X 5.0 including manmade and natural cyber and non-cyber threats, pandemics, and disasters
  • Methodologies and tools for analysis, compliance, and enforcement of law and regulations for safety, security, and/or privacy
  • Methodologies and tools for compliance testing and standardization
  • CAD tools for AI-based cyber-physical systems (CPS)
  • CAD tools for safe, secure, privacy, and law-aware RT-CPS
  • Case studies for AI and machine learning-based RT-CPS
  • Case studies for digital law compliance and regulations in RT-CPS
  • Benchmarks for security, safety, privacy, and/or law in RT-CPS
  • Challenges in modeling, analysis, safety, security, privacy, and law of RT-CPS

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SS02 - Autonomous Vehicles in Industry 5.0

Special Session Organized by

Antonello Venturino, DIMES, Università della Calabria, Italy, and Luigino Filice, DIMEG, Università della Calabria, Italy,

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Focus

This Special Session focuses on the ongoing digitalization in the industry, particularly in the realm of Industry 4.0, which encompasses advancements in Autonomous Vehicles. This transformative process enhances production and industrial automation, leading to more effective and flexible operations. However, digital solutions in manufacturing processes introduce new challenges and concerns that need to be addressed. Rather than replacing Industry 4.0, the Industry 5.0 paradigm builds upon it. The goal of this Special Session is to explore innovative approaches and experiments for the utilization of Autonomous Vehicles in Industry 5.0, which embrace sustainability and a human-centric perspective.

Topics under this track include (but not limited to):
  • Autonomous Vehicles in industrial mobility
  • Map Building and Localization, SLAM
  • Machine Learning for Mobile Robotics
  • Digital Wellbeing induced by autonomous robotics
  • Autonomous Vehicles for a more Sustainable Manufacturing

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SS03 - Technologies for Autonomous Outdoor Logistic Functions

Special Session Organized by

Eike Lyczkowski, SEW-EURODRIVE GmbH &Co KG, Germany, and Wolfgang Kiess, Universit of Applied Sciences Koblenz, Germany, and Frank Schönung, SEW-EURODRIVE GmbH &Co KG, Germany, and Johannes Bleier, SEW-EURODRIVE GmbH &Co KG, Germany, and Sebastian Brack, SEW-EURODRIVE GmbH &Co KG, Germany, and Julia Gärtner, SEW-EURODRIVE GmbH &Co KG, Germany, and Yannick Herrling, SEW-EURODRIVE GmbH &Co KG, Germany, and Lars Münster, SEW-EURODRIVE GmbH &Co KG, Germany, and Daniel Rittershofer, SEW-EURODRIVE GmbH &Co KG, Germany, and Christoph Schlindwein, SEW-EURODRIVE GmbH &Co KG, Germany, and Frank von Schoettler, SEW-EURODRIVE GmbH &Co KG, Germany, and Maximilian Winter, SEW-EURODRIVE GmbH &Co KG, Germany, and Yannick Wunderle, SEW-EURODRIVE GmbH &Co KG, Germany,

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Focus

The ever-growing demand for urban parcel delivery has led to many new solutions for autonomous outdoor logistic functions in unstructured environments and also fosters new use cases like autonomous waste collection. On the factory floor, related transportation tasks are already highly automated, e.g., by autonomous guided vehicles. This session focuses on the challenges when transferring such in-factory technologies to urban settings. This involves new ideas on the processes involved, coping with the related regulatory regimes, employing existing infrastructures, or automating navigation tasks. This session discusses urban last mile logistics on a holistic basis and aims to combine it with the large body of knowledge on intra-logistics and thereby bring together technology, processes, and regulation. Work on prototype and proof-of-concept implementations are highly welcome.

Topics under this track include (but not limited to):
  • Process design for last mile and outdoor logistics
  • Vehicle design in unstructured environments
  • Navigation and localization in outdoor environments
  • Safety of autonomous robots in outdoor environments and crowded areas
  • Functional Safety for classification tasks
  • Operation, evolution, and management of last mile logistics and its vehicles
  • Communication technologies in outdoor environments
  • Regulatory topics and special permits for testing

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SS04 - Capability- and Skill-based Engineering of Manufacturing Systems

Special Session Organized by

Aljosha Köcher, Helmut Schmidt University, Germany, and Kristof Meixner, CDL-SQI, TU Wien, Austria, and Siwara Schmitt, Fraunhofer IESE, Germany, and Fabian Spitzer, University of Applied Sciences Upper Austria, and Michael Winter, RWTH Aachen University, Germany,

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Focus

As customer requirements change more frequently, pursuing flexible and adaptive automation approaches becomes necessary. Such approaches demand an explicit description of a production system's functionality and the products to be manufactured. Recent research has introduced approaches based on capabilities and skills using holistic data models (i.e., ontologies, DSLs, variability models...). While capabilities are understood as specifications of (manufacturing) functions a system can perform, skills are considered to be their executable counterparts (i.e., implementations of functions with an interface using a technology such as OPC UA). To find solutions for customer requirements automatically, required tasks and domain-specific constraints must be matched with capabilities provided by automation components. This can be achieved by various techniques such as AI planning or knowledge graph exploration and reasoning. Process plans can then be orchestrated by combining skills related to capabilities found in the previous step. Finally, simulation and optimization of such process plans can be performed before executing them.

Topics under this track include (but not limited to):
  • Modeling of capabilities, skills and services: Data Modeling, Modeling Languages, Knowledge Graphs, Rule Engines, Knowledge-based Systems, Asset Administration Shell
  • Algorithms to find and match capabilities: Planning, Artificial Intelligence, Capability-task-matching, Knowledge Graph Exploration
  • Skill-based production: Generation/Modeling of process plans, Orchestration, Execution, Optimization
  • Simulation of a proposed plan: Optimization, simulation techniques for skills
  • Engineering methods: Automated code generation, model-based

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SS05 - Evaluation Methods for Autonomous Cyber-Physical Systems' Behavior

Special Session Organized by

Alexander Fay, Ruhr University Bochum, Germany, and Felix Gehlhoff, Helmut Schmidt University Hamburg, Germany, and Artan Markaj, Helmut Schmidt University Hamburg, Germany, and Mehmet Mercangöz, Imperial College London, United Kingdom, and André Scholz, Siemens AG, Germany,

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Focus

Global competition, shorter product life cycles, and highly volatile markets are putting a strain on operations in manufacturing, process, logistics, and energy systems. Many industries are facing a shortage of workers today, and given these trends, production of essential goods as well as the operation of such systems are going to be at risk due to missing workers and operators. To tackle these challenges, a higher degree of autonomy in cyber-physical systems (CPS) operations can be considered. Such autonomous CPS represent technical constructs which make decisions without the intervention of humans. In addition, autonomous CPS can be characterized by the ability to execute processes systematically, the ability to adapt to environmental changes, and the ability to self-govern resources. However, due to these characteristics, the behavior of such systems is not always easily explainable and predictable. Thus, methods for the evaluation of the behavior of such systems are of increasing importance. Evaluating these systems encompasses testing, verifying, diagnosing, and explaining (inter-)actions as well as analyzing performance. Suitable methods can be data-driven (incl. Generative AI) and knowledge-driven as well as simulation-based. Potential use cases can be, for example, a simulation-based selection of the most appropriate goals to follow by autonomous CPS or explaining actions of autonomous CPS to operators.

Topics under this track include (but not limited to):
  • Simulation-based evaluation of autonomous CPS’ behavior
  • Verification of system goals and requirements
  • Testing intelligent control algorithms (multi-agent systems, reinforcement learning, or model-predictive control) for autonomous CPS
  • Data-driven methods for autonomous CPS’ identification and adaption
  • Real-time diagnosis and decision-making in autonomous CPS’ operation
  • Integration of Explainable AI (XAI) for enhanced autonomous CPS’ transparency
  • Real-time decision support approaches for autonomous CPS’ supervision
  • Evaluation of human-autonomy interaction in remote and autonomous operation
  • (Real-time) Safety and regulatory compliance evaluation of autonomous CPS
  • Performance and test-beds for the evaluation of autonomous CPS
  • Evaluation of degrees of autonomy in autonomous CPS

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SS06 - Generative System Design for Autonomous Systems

Special Session Organized by

Shahram Eivazi, Festo, Germany, and Jan Seyler, Festo, Germany,

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Focus

In an era where engineering complexity is escalating, the traditional methodologies for system design, especially in autonomous systems, are facing significant challenges. The advent of generative system design introduces a paradigm shift, promising to revolutionize the way we approach engineering tasks and processes. This Special Session on Generative System Design for Autonomous Systems at the forthcoming ETFA conference seeks to explore the frontier of generative methodologies in engineering. With an emphasis on generative AI, including evolutionary algorithms, generative networks, reinforcement learning, and large language models, this session is poised to showcase cutting-edge methodologies, insightful case studies, and the latest trends in the field. From conceptual designs to system-level integrations and component optimizations, the session will cover an extensive range of topics, emphasizing the transformative impact of generative system design in autonomous systems. We invite submissions that focus on, but are not limited to, the following topics:

Topics under this track include (but not limited to):
  • Modelling of Automation Tasks and Processes: Innovative approaches to representing and understanding complex automation tasks and processes within autonomous systems.
  • Simulation Techniques for Data Generation or Process Optimization: Advanced simulation methodologies that contribute to efficient data generation, system testing, or process optimization in autonomous systems.
  • Large Language Models for System Synthesis: Exploration of how large language models can be leveraged for the synthesis and integration of complex autonomous systems.
  • Neural Networks and Reinforcement Learning for Engineering Design: Cutting-edge applications of neural networks and reinforcement learning in the context of engineering design, focusing on autonomous systems.
  • Design, Topology, and Process Optimization: Novel strategies for optimizing the design, topology, and operational processes of autonomous systems, ensuring efficiency and adaptability.
  • Advanced Motion and Task Planning in Autonomous Systems: This topic will explore innovative strategies and algorithms in motion planning and task execution within autonomous systems, emphasizing efficiency, safety, and adaptability in dynamic environments.
  • Integrating Symbolic and Subsymbolic AI for Enhanced System Intelligence: This area will focus on the synergy between symbolic AI, with its rule-based processing and logical reasoning, and subsymbolic AI, such as neural networks, to create more robust and intelligent autonomous systems through knowledge-guided machine learning.

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SS07 - Software Engineering for Cyber-Physical Production Systems (SECPPS)

Special Session Organized by

Kevin Feichtinger, Karlsruhe Institute of Technology, Germany, and Kristof Meixner, TU Wien, Austria, and Felix Rinker, TU Wien, Austria, and Klaus Schmid, University of Hildesheim, Germany,

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Focus

With the emergence of Cyber-Physical Production Systems (CPPSs), systems engineers are facing a dramatic increase in the complexity of the development and operation of such systems. However, software plays a crucial role in the effective and efficient operation of CPPSs. Yet, Software Engineering for CPPSs poses several challenges, such as the integration of multiple disciplines, the unclear semantics and variability of engineering artifacts, support of AI for CPPSs, or the continuous testing and deployment to heterogeneous systems. Hence, it requires novel approaches to a large range of problems to address these challenges. More comprehensive and systematic views on all aspects of CPPSs and their development are required. The Special Session on Software Engineering for Cyber-Physical Production Systems aims to discuss challenges for software engineering approaches and technologies to CPPSs, including their adoption, and highlight novel methods for the design of CPPS software.

Topics under this track include (but not limited to):
  • Model-based software and languages for the engineering and operation of CPPSs (e.g., DSL)
  • Operation, evolution, and management of CPPS software (e.g., DevOps, agile methods)
  • Approaches to monitor and improve CPPSs (e.g., Digital Twins, metrics, self-adaptability)
  • Interdisciplinary collaboration in the engineering and operation of CPPS software
  • Security, resilience and sustainability of CPPS software by design
  • Testing, validation and verification of CPPSs
  • Artificial intelligence and LLMs for the engineering and operation of CPPSs
  • Software engineering education for CPPS engineers

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SS08 - Exploring the limits of Time Sensitive Networking (TSN)

Special Session Organized by

Elena Ferrari, University of Padova, Italy, and Alberto Morato, National Research Council of Italy (CNR‐IEIIT), Italy, and Julian Proenza, Universitat de les Illes Balears, Spain, and Corrado Puligheddu, Politecnico di Torino, Italy,

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Focus

This special session aims to explore the advancements and challenges in deterministic networks, focusing on Time-Sensitive Networking (TSN). TSN identifies standards, algorithms, and protocols aiming to enhance the capabilities of communication networks for time-critical real-time dependable applications through accurate time synchronization, hard, non-negotiable time boundaries for transmission latency, and fault tolerance mechanisms. TSN standards have triggered a significant amount of research that explores the limits of the technology and proposes techniques to go beyond them in four basic domains; real-time response of mixed traffic, fault tolerance, network configuration, and the practical use of this technology in many application areas. For instance, recent developments in this field have brought TSN to wireless networks such as 3GPP 5G New Radio and IEEE 802.11 Wi-Fi. The application of TSN in hybrid networks is a captivating subject of study, as it would enable time-sensitive applications such as extended reality (XR), time-critical sensor networks, and real-time remote control in industrial, robotics, avionics, aerospace, and automotive devices. The session is open to all research aimed at exploring and going beyond the limits of this technology thereby showing its potential.

Topics under this track include (but not limited to):
  • Scheduling algorithms
  • Fault-tolerance mechanisms for highly-dependable TSN networks
  • Configuration of complex TSN networks
  • Novel algorithms and protocols for wireless TSN
  • Integration of TSN on Wi-Fi and 5G New Radio
  • Innovative solutions for redundancy and dynamic routing
  • Optimal network topology design
  • Methodologies for metrological characterization of TSN networks
  • Formal methods (FM) for the design of efficient, reliable, and optimized hybrid TSN networks
  • Development of simulation models
  • Adoption of TSN in robotics applications
  • Adoption of TSN in industrial applications
  • Adoption of TSN in Smart/Micro Grids

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SS09 - Industrial Cybersecurity Methods and Technologies

Special Session Organized by

Paulo C. Bartolomeu, University of Aveiro (Portugal), and Amjad Gawanmeh, University of Dubai (UAE), and Stefano Marrone, University of Campania “Luigi Vanvitelli” (Italy),

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Focus

Industrial cybersecurity has become a key research topic in recent years due to the massive connectivity brought by the Internet of Things and the rise of cyberattacks against industrial assets. While fostering contemporary applications and use cases, ubiquitous Internet access has also exposed legacy operational technologies to new and challenging security threats that must be addressed. This Special Session focuses on novel security, safety, and privacy-enhancing technologies for current and future industrial applications.

Topics under this track include (but not limited to):
  • Security, safety, or privacy-enhancing technologies in industrial systems
  • Modeling of cybersecurity threats
  • Applications of Artificial Intelligence in cybersecurity of industrial systems
  • Applications of distributed ledger technologies/blockchains in Industry 4.0
  • Self-sovereign identity for M2M and decentralized device-to-device communication
  • Hardware advances for securing Industrial devices and networks
  • Quantitative evaluation and/or interconnections among non-functional aspects (e.g., reliability vs. safety, security vs. performance)
  • Run-time methods and technologies for Complex Event Detection systems
  • Software engineering methods and techniques for high dependable control systems
  • Security and privacy issues in CPS for industry systems
  • Cyber-Physical Attacks and Countermeasures
  • Real-time Threat Detection and Response for CPS and industry systems
  • Case studies / lessons learned of security, safety, or privacy assessments of industrial systems

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SS10 - Edge-to-Cloud Data-driven Distributed Industrial Cyber Physical Systems

Special Session Organized by

Udayanto Dwi Atmojo, Dept. of Electrical Engineering and Automation, Aalto University, Finland, and Rui Pinto, FEUP University of Porto, Portugal, and Valeriy Vyatkin, Dept. of Electrical Engineering and Automation, Aalto University, Finland, and Pouria Sayyad Khodashenas, Huawei Technologies Sweden, Sweden,

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Focus

Cloud and edge computing provide new opportunities in exploiting industrial data and decision-making within industrial cyber-physical systems. For industrial sectors with a high degree of safety and resilience, they require mechanisms and approaches that achieve the right balance in processing, analytics, and control/automation across the cloud, edge, and IoT computing continuum to fulfill real-time, reliability, and cybersecurity requirements. As such, computing, networking (such as 5G), and data storage technologies require novel enablers to establish a high level of flexibility, data governance that facilitate trustworthy data sharing, distributed intelligence, and autonomy. Increased challenges and complexity are foreseen as emerging scenarios are increasingly cross-sector.

Topics under this track include (but not limited to):
  • Trustworthy (including, but not limited to: security, privacy, safety, etc) assurance mechanisms, methods for industrial cyber-physical systems
  • Edge artificial intelligence / Edge AI for industrial cyber-physical systems
  • Zero-touch resource allocation, orchestration, network management for edge-cloud enabled industrial cyber-physical systems
  • Enhancements, novel middleware, deployment strategies for advanced connectivity technologies (e.g., 5G NPN, TSN integration to 5G, etc) in edge-cloud enabled industrial cyber-physical systems
  • Interoperability measures (e.g., semantics, data model, etc) for industrial cyber-physical systems, also in cross-sector cases, e.g., Asset administration shell (AAS)
  • Quantum-based algorithms, communications, methods, simulations across IoT-edge-cloud continuum for industrial cyber-physical systems
  • Federated, distributed intelligence across IoT-edge-cloud continuum for industrial cyber-physical systems.
  • Fault tolerance, resilience mechanisms across IoT-edge-cloud continuum for industrial cyber-physical systems
  • Generative, foundational models and their applications across IoT-edge-cloud continuum for industrial cyber-physical systems
  • Methods, mechanisms, technologies for trustworthy data sharing involving edge-cloud-IoT continuum of industrial cyber-physical systems.
  • Edge-enabled analytics, decision making, control and automation for industrial cyber-physical systems
  • Eco-aware, sustainability, energy efficiency technologies, methods, mechanisms for industrial cyber-physical systems utilizing edge-cloud computing continuum
  • Testbeds, research and pilot infrastructures for testing, validation, demonstration of edge-cloud computing, edge AI considering industrial cyber-physical systems setting.
  • Performance evaluation, testing, validation, demonstration of edge-cloud computing, edge AI considering industrial cyber-physical systems setting.
  • Methods, mechanisms for self-X (self-healing, self-organization, self-repair, etc) considering edge-cloud computing continuum in industrial cyber-physical systems setting.
  • Methods, approaches for engineering edge-cloud computing enabled industrial cyber-physical systems.
  • Education on edge-cloud computing for industrial cyber-physical systems

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SS11 - Automated Testing and Simulation of Converged Automation Networks

Special Session Organized by

Dirk Schulz, ABB AG Corporate Research Center, Germany, and Amin Shahraki, ABB AG Corporate Research Center, Germany,

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Focus

Distributed control systems (DCS) are responsible for the safe and uninterrupted automation of large-scale industrial production systems, and automation functions undergo rigorous testing before process start-up. Automation networks are an integral part of the mission-critical infrastructure of such DCSes. With the network convergence of IT, automation, and telecom applications, the complexity of providing QoS and cybersecurity for these applications is increasing, and similarly thorough testing as for automation is desirable. The area of automated and virtual/hybrid network testing in this context is a little worked field to which we would like to focus the attention of the scientific community.

Topics under this track include (but not limited to):
  • Automated generation of network test cases for automation systems
  • Automated execution of network test cases, i.e. generation, injection, capture, and analysis of traffic corresponding to the test cases
  • VNFs for usage in network emulation for testing purposes
  • Automated setup of virtual or hybrid network emulation and/or simulation environments
  • Achievable coverage and fidelity of such testing approaches

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SS12 - Interplay Between Communications and Computations in Industrial Cyber-Physical Systems

Special Session Organized by

Indrakshi Dey, Walton Institute for Information and Communication Systems Science, Ireland, and Arun Narayanan, LUT University, Finland, and Nicola Marchetti, Trinity College Dublin, Ireland, and Pedro Nardelli, LUT University, Finland,

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Focus

This call for papers invites submissions focusing on the cutting-edge developments in data-driven wireless connectivity, poised to transform monitoring, control, and efficiency within cyber-physical systems (CPS). Papers should offer innovative, interdisciplinary strategies utilizing data to enhance sensing, control, and resource allocation across interconnected systems. Papers should present original research that tackles the evolving demands of contemporary industrial CPS, emphasizing reliability, sustainability, and resilience against disruptions, thus paving the way for further technological breakthroughs in this domain.

Topics under this track include (but not limited to):
  • Resilient learning methods to deal with communication failures and incomplete data streams, including, but not limited to
  • Resilience against system failures such as transmission failures, channel distortion, or asynchronization
  • Security against malicious actors, for example, malicious data injection, deliberate signal distortion, etc.
  • Novel edge computing solutions to enable scalable interactions between distributed industrial cyber-physical systems, including
  • Architectures for specific applications and purposes, e.g., energy-aware industrial manufacturing
  • Machine Learning frameworks for efficient and scalable computations
  • Latency, data and network availability, and resource allocation in the case of heterogeneous computation/storage capabilities
  • Privacy and security of processes and systems for resource allocation in industrial cyber-physical systems
  • Data-driven control techniques for interconnected industrial cyber-physical systems
  • Scalable data-driven techniques for efficient computations and control of well-defined tasks
  • Learning algorithms and methods deploying cutting-edge communication protocols like 5G, LPWAN, or satellite IoT for collaborative tasks
  • New data processing methods for imputation, aggregation, or fusion for decision-making support or autonomous operation for monitoring and control.
  • Real-world applications of energy-aware collaborative industrial cyber-physical systems
  • Practical demonstrations of collaborative industrial cyber-physical systems that achieve high renewable energy usage
  • Energy-aware industrial cyber-physical systems, including challenges and opportunities
  • New semantic approaches to (wireless) communications in industrial cyber-physical systems
  • Semantic communication techniques for industrial process control
  • Age, Relevance and Value of information for process monitoring and environment awareness
  • Surveys and review papers on synergies between communications and computations in cyber physical systems

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