Current Projects

Research Projects at the Cyber-Physical Systems Group

USA-funded Projects

CyberHeart

CyberHeart

Funding: USA-NSF

Partners: Carnegie Mellon University, University of Maryland, Stony Brook University, Georgia Tech, Rochester Institute of Technology, University of Pennsylvania, Fraunhofer Center for Experimental Software Engineering, Food and Drug Administration (FDA)

Time Frame: started 01. 01. 2015

Contact Persons: Radu Grosu

Research Team: Ezio Bartocci, Radu Grosu, Scott A. Smolka

The NSF-CPS-Frontiers project CyberHeart is part of the NSF’s initiative to advance the state-of-the-art in Cyber-Physical Systems (CPS): engineered systems that are built from, and depend upon, the seamless integration of computation and physical components. The main goal of the project is to develop far more realistic cardiac device models and controllers than the ones that currently exist. The challenge is in the sheer scale of the human’s cardiac CPS: Six billion cells arranged in a very sophisticated network interact with each other in order to synchronise and contract such that they collectively achieve what is commonly called a heart beat, pumping the blood through the entire body. The CyberHeart platform will provide a basis to test and validate medical devices faster and at a far lower cost than existing methods. It will also provide a platform for designing optimal, patient-specific device therapies, thereby lowering the risk to the patient. CyberHeart includes collaborators from nine leading universities and centres: CMU, RIT, UM, GTech, UPenn, FC-ESE, SBU, TUW and FDA.

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EU-funded Projects

Productive4.0

Productive4.0

Funding: EU-ECSEL

Partners: 114 organisations

Time Frame: started 01. 05. 2017

Contact Persons: Radu Grosu, Haris Isakovic

Research Team: Haris Isakovic

Electronics and ICT as enabler for digital industry1 and optimized supply chain management covering the entire product lifecycle

The main objective of Productive4.0 is to achieve significant improvement in digitalizing the European industry by means of electronics and ICT. Ultimately, the project aims at suitability for everyday application across all industrial sectors – up to TRL8. It addresses various industrial domains with one single approach, that of digitalisation. What makes the project unique is the holistic system approach of consistently focusing on the three main pillars: digital production, supply chain networks and product lifecycle management.This is part of the new concept of introducing seamless automation and network solutions as well as enhancing the transparency of data, their consistence, flexibility and overall efficiency. Currently, such a complex project can only be realised in ECSEL.The well balanced consortium consists of 45% AENEAS, 30% ARTEMIS-IA and 25% EPOSS partners, thus bringing together all ECSEL communities. Representing over 100 relevant partners from 19 EU-member states and associated countries, it is a European project, indeed.
AFarCloud

AFarCloud

Funding: EU-ECSEL Joint Undertaking

Partners: 59 organisations

Time Frame: started 01. 09. 2018

Contact Persons: Christian Hirsch, Radu Grosu

Research Team: Christian Hirsch, Radu Grosu

Farming is facing many economic challenges in terms of productivity and cost-effectiveness, as well as an increasing labour shortage partly due to depopulation of rural areas. Reliable detection, accurate identification and proper quantification of pathogens affecting both plant and animal health, must be kept under control to reduce unnecessary costs, trade disruptions and even human health risks.

AFarCloud addresses the urgent need for a holistic and systematic approach. It will provide a distributed platform for autonomous farming, which will allow the integration and cooperation of Cyber Physical Systems in real-time for increased agriculture efficiency, productivity, animal health, food quality and reduced farm labour costs. This platform will be integrated with farm management software and will support monitoring and decision-making, based on big data and real time data mining techniques.

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iDev40 - Enabling Artificial Intelligence in the European Electronic Component and Systems Industry

iDev40 - Enabling Artificial Intelligence in the European Electronic Component and Systems Industry

Funding: EU-ECSEL Joint Undertaking

Time Frame: started 01. 05. 2018

Contact Persons: Hamidreza Mahyar, Radu Grosu

Research Team: Hamidreza Mahyar, Radu Grosu, Ramin Mohammad Hasani

iDev40 focuses on “digitally connecting” value chains to facilitate and strengthen the innovation capacity of large and small European Electronic Components and System actors for sustainably competitive Electronic Components and Systems “Made in Europe”. Digitalization in integrated product development and production as well as along value chains (digital twin) is the key aspect of the iDev40 project. Linking the digital and the real world with new Industry 4.0 technologies, smarter, more flexible development and production processes are realized as well as a real-time communication via the Internet of Things between value chain partners. These new technologies include data centered learning approaches, cyber physical system based platforms connecting production processes from different sites, knowledge/IP sharing and data protection methods, holistic data validation and exploitation from heterogeneous data sources. The socio-technical context is considered through a human centered knowledge base. We aim to utilize Artificial Intelligence (AI) and Deep Learning (DL) techniques to semantically and automatically enrich data with properties which enable secure storage, tailored protection and validation of data. By integrating design and production data the rate of disconnected data sets will be reduced, which will lead to a decrease in data retrieval time and thus enhance the overall data quality. The elaboration of these technology targets is addressed by (1) Data management, sharing and storage; (2) Gathering, curating, pre-processing and updating/validating knowledge; and (3) Semantical annotation and enrichments of data by adopting AI and DL principles.

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AT-funded Projects

IoT4CPS: Trustworthy IoT for CPS

IoT4CPS: Trustworthy IoT for CPS

Funding: AT-FFG

Partners: TU Wien, Austrian Institut of Technology (AIT), Institute of Science and Technology (IST), AVL List GmbH, Donau Uni Krems, Infineon Technologies AG, JKU Linz, Joanneum, NOKIA Österreich, NXP, Salzburg Research, SBA Research, SCCH, Siemens AG Österreich, TTTech Computertechnik AG, TU Graz, X-Net Services GmbH

Time Frame: started 01. 12. 2017

Contact Persons: Ezio Bartocci, Radu Grosu, Muhammad Shafique

Research Team: Ezio Bartocci, Radu Grosu, Muhammad Shafique, Faiq Khalid

IoT4CPS will develop guidelines, methods and tools to enable safe and secure IoT-based applications for automated driving and for smart production. The project will address safety and security aspects in a holistic approach both along the specific value chains and the product life cycles. To ensure the outreach of the project activities and results, the relevant stakeholders will be involved throughout the project and results will be disseminated to expert groups and standardization bodies. IoT4CPS will support digitalization along the entire product lifecycle, leading to a time-to-market acceleration for connected and autonomous vehicles. IoT4CPS will provide innovative components, leading to efficiency increases for the deployment of autonomous driving functions and in smart production environments, which will be validated in a vehicle and in a smart production demonstrator.

CPS/IoT Ecosystem: Preparing Austria for the Next Digital Revolution

CPS/IoT Ecosystem: Preparing Austria for the Next Digital Revolution

Funding: AT-BMWFW: HRSM Grant

Partners: TU Wien, Austrian Institut of Technology (AIT), Institute of Science and Technology (IST)

Time Frame: started 01. 06. 2017

Contact Persons: Haris Isakovic, Radu Grosu

Research Team: Radu Grosu, Manfred Gruber, Thomas A. Henzinger, Schahram Dustdar, Dejan Nickovic, Gerti Kappel

Cyber-physical systems (CPS) are spatially-distributed, time-sensitive, multiscale networked embedded systems, connecting the physical world to the cyber world through sensors and actuators. The Internet of Things (IoT) is the backbone of CPS. It connects the Sensors and Actuators to the nearby Gateways and the Gateways to the Fog and the Cloud. The Fog resembles the human spine, providing fast and adequate response to imminent situations. The Cloud resembles the human brain, providing large storage and analytic capabilities.

In this project we will make Austria a major player in Real-Time (RT) CPS/IoT, by building on its national strengths. In collaboration with renowned Austrian companies such as TTTech or ams AG, we will create an RT CPS/IoT-Ecosystem with more than 5000 sensors and actuators, where we can all experiment with new ideas, and develop this way an Austrian know-how. This effort will be aligned with the strategic Austrian initiatives, Industry 4.0 and Silicon-Austria. The ecosystem will be distributed across Vienna in collaboration with our partners at AIT and IST.

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LogiCS - Logical Methods in Computer Science

LogiCS - Logical Methods in Computer Science

Funding: AT-FWF

Partners: Vienna University of Technology, Graz University of Technology, Johannes Kepler University Linz, Austrian-wide National Research Network on Rigorous Systems Engineering (RiSE), Vienna Center for Logic and Algorithms (VCLA)

Time Frame: started 01. 01. 2014

Contact Persons: Sophie Grünbacher, Radu Grosu

Research Team: Sophie Grünbacher, Ezio Bartocci, Radu Grosu, Stefan Szeider

Logical Methods in Computer Science (LogiCS) research project lies in the intersection of two broad areas: Databases and Artificial Intelligence, where logic is used to model, store, analyze and predict information about the outside world including the Internet. And the second one is Verification, where logic is used to model, analyze and construct computer programs themselves. The logical and algorithmic questions which underlie both application areas are studied in the area of Computational Logic. In the LogiCS curriculum, all three directions are prominently represented. Moreover our commitment to international and interdisciplinary collaboration is prerequisite for today’s challenges: Computer science has reached a state where many of the basic engineering questions are reasonably well understood. Many of the big open research questions, however, require computers to perform non-trivial reasoning tasks that permeate computer science, other sciences such as economy, physics, medicine and biology, as well as every-day life. Nowadays, there are a lot of important and interesting research questions in the rapidly expanding domains of cyber-physical (CPS) and biological systems (BS). For instance: ‘How does one formally specify emergent behavior of a system?’ or ‘How does one efficiently predict and detect its onset?’ It is obvious that the formal specification of emergent behavior is a great challenge: first, the logic has to be able to capture temporal properties, which manifest themselves both in the time and in the (dual) frequency domains. Second, the logic has to be able to capture spatial properties, which manifest themselves both in the space and in the (dual) spatial-frequency domains. So right now we are trying to extend temporal logic with frequency domain properties based on different forms of transforms: Fourier, Gabor, Wavelet and to develop a formalism to describe various significant patterns based on combinations of ideas from spatial/temporal logics and signal processing.

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COCO: Control Equivalence for Cyber-Physical Models

COCO: Control Equivalence for Cyber-Physical Models

Funding: AT-FWF: Lise Meitner Fellowship

Partners: TU Wien (coordinator), IMT Lucca (collaborator)

Time Frame: started 01. 08. 2018

Contact Persons: Max Tschaikowski, Radu Grosu

Research Team: Max Tschaikowski, Radu Grosu

Nonlinear continuous and hybrid dynamical systems are of paramount importance in the modeling of biochemical, cyber-physical and dependable systems. Unfortunately, their precise parametrization is often not possible due to finite-precision measurements or lack of information. Hence, in order to ensure safety in the presence of parameters that are subject to uncertainty, it thus becomes necessary to formally approximate the underlying dynamical system. A possible example may be, for instance, the task of verifying that the autopilot keeps the airplane in stable flight in the presence of realistic turbulence.

Despite the fact that the computation of tight formal approximations received a lot of attention, it remains computationally demanding in the case of nonlinear dynamics. A universal approach for the simplification of difficult problems is that of model reduction where the idea is to formally relate the original problem to a smaller one which can be solved more efficiently. While model reduction techniques have been applied in the context of approximation problems in the past, to the best of our knowledge, no efficient reduction algorithms are available in the case of nonlinear dynamics. The main goal of the project is to close this gap by identifying formal approximation problems as optimal control problems which can be reduced efficiently.