AI4DT&CP

The second Workshop on
AI for Digital Twins and Cyber-physical applications


In conjunction with IJCAI 2024
the 33rd International Joint Conference on Artificial Intelligence

August 3-9 2024, Jeju, South Korea

Topics of interest

Call for papers

AI4DT&CP


The availability of easy-to-deploy sensors and the general advances in the Internet of Things (IoT) technology have led to the emergence of new applications that seamlessly blend the physical and digital worlds. Notwithstanding this trend, there are still open issues. A major one, due to the heterogeneity of the several models involved, is dealing with the complexity of the physical world to develop and deploy intelligent services that continuously perceive and learn from data coming from the environment.
The idea gained traction among both academic institutions and industry players, revitalising the Digital Twin technology that enables the creation of virtual replicas of physical objects by mirroring their properties, data and behaviors and enabling new intelligent and augmented functionalities such as modelling, simulation, and cognitive capabilities.
We believe that Artificial Intelligence (AI) will transform the field of Digital Twin technology by enabling the creation of intelligent virtual replicas that may offer smart services and lead to adaptive AI in cyber-physical environments.
Overall, AI can be used to enhance the performance, safety, and security of Digital Twin and cyber-physical systems by making them more intelligent, adaptive, and autonomous. The results can be better control, optimisation, and prediction of the Cyber-Physical systems. Digital Twin and cyber-physical systems can be enhanced with AI in several ways since AI enables real-time monitoring and control of physical systems with the possibility of delivering intelligent services with applications in several domains, such as:
  • Predictive modelling: AI-powered digital twins can predict the behaviour of physical systems under different conditions, helping to identify potential issues or inefficiencies in the physical system before they occur.
  • Anomaly detection: AI-powered digital twins can analyse sensor data from the physical system in real-time, using machine learning techniques to identify anomalies or deviations from normal behaviour.
  • Digital Human Replica: Building virtual replicas of humans that reproduce and model both outer and inner aspects of a human being, such as physical and physiological characteristics, personality, sensitivities, thoughts and skills.
  • Optimisation: AI-powered digital twins can analyse sensor data and other inputs to optimise the performance of the physical system (e.g., by adjusting the control parameters to minimise energy consumption or maximise production efficiency).
  • Autonomous control: AI-powered digital twins can be used to control a physical system autonomously, using sensor data and other inputs to make real-time decisions.
  • Safety and security: AI-powered digital twins can be used to monitor and analyse sensor data to detect security threats or unsafe conditions in the physical system and to trigger appropriate responses.
  • Big Data Applications: Big data frameworks can be leveraged to make sense of huge data collections and provide the digital twins with further features, analysis, graphs.
At the same time, incorporating machine learning models into digital twin systems can be critical when monitoring or controlling critical systems.

Machine Learning Operations (MLOps) approaches are attracting increasing interest to ensure that intelligent models are deployed robustly and reliably, especially when exploiting Continual Learning or Reinforcement Learning techniques.
The workshop aims to bring together experts in the fields of Artificial Intelligence, Digital Twin technology, and Cyber-Physical systems to explore the latest developments and best practices in the use of AI-based digital twins for a wide range of cyber-physical services and applications.

Topics of interest

Topics of interest of AI4DT&CP include, but are not limited to, the following:
  • What-if scenarios with Cyber-Physical applications
  • MLOps in Cyber-Physical systems
  • Digital Twin intelligence management
  • Digital Twins modelling for AI for physical augmentation
  • Cyber-Physical application and MLOps for anomaly detection
  • Digital Twins for synthetic data generation in Cyber-Physical applications
  • Predictive Maintenance in Cyber-Physical systems
  • Intelligent Digital Twins for optimisation use cases (Smart cities, smart buildings, environmental monitoring)
  • Digital human replica with AI
  • Cyber-Physical application with AI in healthcare
  • Digital Twins for continual learning scenarios
  • Reinforcement Learning in Cyber-Physical applications

Program

The workshop will be held on August 5th during IJCAI 2024.

August 5th

Welcome and Opening Remarks

Towards Digital Twin-based Operation and Maintenance: A Virtual Assistant Framework for Creating Guidelines According to Managers’ Requirements

Sheng Bao and Hangdong Bu.

Digital Twin Orchestration: Framework and Smart City Applications

Do-Van Nguyen, Minh-Son Dao and Koji Zettsu

Coffee break

On-Edge Implemented Machine-Learning Based Synthetic Flame Detector For Gas Turbine Operation

Valentina Gori, Kanika Goyal, Tiziano Roma, Gianni Bagni, Riccardo Carta, Bruno Giunta, Giovanni De Magistris and Giovanni Tonno

Knowledge representation for neuro-symbolic digital building twin querying/span>

Stephane Reynaud, Anthony Dumas and Ana Roxin

Closing remarks

Lunch break

Free discussion & networking

Second coffee break


Important dates

Submission deadline: May 5,2024 May 24,2024
Paper notification: June 4,2024
Camera-ready: July 5,2024
Workshop: August 3-9,2024

Submission

Papers can be submitted as PDF using EasyChair:
https://easychair.org/my/conference?conf=ai4dtcp

Papers must comply with the CEURART paper style (1 column) and can fall in one of the following categories:
  • Full research papers(minimum 7 pages)
  • Short research papers(4-6 pages)
  • Position papers(2 pages)

The CEURART template can be found on Overleaf at:
https://it.overleaf.com/latex/templates/template-for-submissions-to-ceur-workshop-proceedings-ceur-ws-dot-org/wqyfdgftmcfw

Accepted papers (after blind review of at least 3 experts) will be included in a volume of the CEUR Workshop Proceedings. We are also planning to organize a special issue and the authors of the most interesting and relevant papers will be invited to submit and extended manuscript.
At least one author of each accepted paper must travel to the IJCAI venue in person
Multiple submission of the same paper to more IJCAI workshops are forbidden

Organization

Workshop organizers


Speaker 1

Gianfranco Lombardo

University of Parma, Italy

Speaker 1

Felix Theusch

German Research Center for AI (DFKI), Germany

Speaker 2

Marco Picone

University of Modena and Reggio Emilia, Italy

Speaker 3

Diego Reforgiato Recupero

University of Cagliari, Italy

Speaker 4

Giuseppe Vizzari

University of Milano-Bicocca, Italy

Program Committee


  • Panos Pardalos - University of Florida, USA
  • Phu Nguyen - SINTEF, Norway
  • Ana Roxin, Universitè de Bourgogne, France
  • Maria Chiara Magnanini, Polytechnic of Milan, Italy
  • Ralph Bergmann - University of Trier, Germany
  • Greta Dolcetti - Ca' Foscari University of Venice, Italy
  • George Adosoglou - University of Florida, USA
  • Mattia Pellegrino - University of Parma, Italy
  • Seonho Park - Georgia Tech, USA
  • Agostino Poggi - University of Parma, Italy
  • Alam Mehwish, Telecom Paris, France
  • Marco Lippi - University of Modena and Reggio Emilia, Italy
  • Alessandro Ricci - University of Bologna, Italy
  • Torben Weis, University Duisburg-Essen, Germany
  • Fabrizio De Vita - University of Messina, Italy
  • Samy El-Tawab, James Madison University, Harrisonburg, USA
  • Ruben Alonso - R2M Solution s.r.l., Italy
  • Carlo Giannelli - University of Ferrara, Italy

Previous editions

Previous editions of the AI4DT&CP Workshop:
  • IJCAI 2023, August 19th 2023, Macau S.A.R - Website

Contact for information

E-mail: gianfranco.lombardo@unipr.it