Ongoing Projects

CompEAS-BSW1 - Compositional Embedded Automotive Systems - Basic Software

The goal of this project is to investigate dependability aspects and the dynamic composition of software and hardware of complex computer platforms or embedded automotive systems (EAS) across the entire system stack. More information

CompEAS-HW1 - Compositional Embedded Automotive Systems - Hardware

The execution of software has a significant impact on various runtime characteristics of the hardware. Software critically influences energy consumption, thermal development, or the electromagnetic behavior of a CPU/MCU. While EMC analyses can be used for side-channel attacks, critical temperature patterns and LoadJumps or PowerPeaks can lead to malfuncitons. The new topic "Optimization of processor power characteristics in software" shall be dedicated to the avoidance of LoadJumps and PowerPeaks. More information

CORVETTE - Cognitive sensing for vehicle fleet driven data services

Project CORVETTE aims to develop a software infrastructure for cognitive monitoring of vehicle fleets, which enables measurement, assessment, interpretation and use of vehicle data for diverse data-driven services. More Information

DiSEL - Digitization of services, equipment and logistics

As part of the FFG frontrunner project DiSEL "Digitization of Services, Equipment and Logistics" the Institute for Technical Informatics will support the project with its expertise in the following areas: Specification of the requirements and the definition of the system architecture according to the desired requirements at system level for the digitization of bulk material unloading using sensors / heavy-duty robotics and implementation of sub-modules. Integration of additional sensors (e.g. cameras) and algorithms for predictive maintenance and life cycle optimization in the new system architecture. In DiSEL, students are involved in bachelor theses, seminars / projects and master theses (with employment). More information

Embedded Operating Systems

Vehicular networks that wirelessly connect vehicles, infrastructure, and pedestrians will be the communication backbone for future transportation. Networked smart, semi-automatic and fully autonomous vehicles will rely on shared information, distributed intelligence, and joint actions to optimize traffic/logistics, reduce pollution, and increase road safety. However, great dynamics, continuously changing network topolgies, and heterogeneous devices make dependable communication hard and demand for self-organizing radio protocols at all layers of the communication stack. This project aims on researching the foundations and practical application of self-organizing radio protocols for massively dynamic networks of mobile devices. Thus, nature-inspired techniques for medium acces control are equally important as managing multi-hop communication. More Information

E-MINDS - Embedded Intelligence for wireless communication services

The goal of this project is to develop methods and toolchains that enable the training and deployment of AI/MI models for resource-constrained embedded devices to enable the future use of reliable embedded intelligence in cognitive products and production systems. Within the project, the developed methods and toolchains will be applied and demonstrated in the context of selected cognitive wireless sensing case studies. More information

ENHANCE-UWB - Benchmarking and advancing localization and communication performance of UWB systems in harsh environments

The ENHANCE-UWB project aims to develop a testbed allowing for the reproducible study of UWB transmissions in complex application environments. The developed testbed should also allow benchmarking of communication performance in the presence of co-located wireless devices sharing the same spectrum, and allow experimentation of non-line-of-sight conditions. More Information

EU - OpenInnoTrain - Open Innovation – Research Translation and Applied Knowledge Exchange in Practice through University-Industry-Cooperation

The overarching objective of OPEN-INNO-Train is to form an international and inter-sectoral network of organisations collaboratively working on the joint research field of Open Innovation, University-Industry Cooperation and Research Translation. To facilitate Knowledge Development and Sharing in four contemporary areas - FinTech, Industry 4.0, CleanTech, FoodTech. For globally interconnected societies, scientific research has the potential to foster yet unrealised economic growth, competitiveness, and wellbeing. The conversion of research outputs into tangible outcomes, and, ultimately, sustainable impact is critically important and needs optimising. The process of converting research findings into economic and social benefits appears increasingly complex at a time when researchers often work in multidisciplinary teams, in a context of Open Innovation when cooperating with industry and other stakeholders. Illuminating it from the perspective of Research Translation, an approach increasingly gaining traction in the specific setting of University-Industry Collaboration, OPEN-INNO-TRAIN aims at opening the black box of knowledge conversion processes to generate and apply new insights from those four industry areas. Furthermore, OPEN-INNO-TRAIN encapsulates the development of robust Research Translation tools capable of facilitating the translation process of multidisciplinary research findings for the generation of impact. Combining scientific excellence from European and international universities, Research and Technology Organisations with hands on expertise from pioneering companies, OPEN-INNO-TRAIN will spearhead this sustainable venture using digital innovation hubs, co-tutelle, industrial PhDs, PPPs and training measures to encourage international cooperation among researchers and industry practitioners across disciplines whose final aim is to holistically foster, enhance and sustain over time the application of good research translation practices. More Information

EU - TEACHING - A computing toolkit for building efficient autonomous applications leveraging humanistic intelligence

Industry and society are experiencing the transformational impact of the autonomous systems revolution, empowered by automation capabilities offered by Artificial Intelligence (AI). Cyber-physical Systems of Systems (CPSoS) define a multi-faceted and dynamic environment where autonomy is fundamental to govern the complexity of interactions between the virtual and physical worlds with minimal human intervention. However, even when the most advanced degree of autonomy is exercised, the human is a variable which cannot be left out of the CPSoS equation, particularly in safety critical scenarios like autonomous transportation. TEACHING puts forward a vision of humans at the centre of autonomous CPSoS, by embracing the concept of Humanistic Intelligence, where the cybernetic and biological entities cooperate in a mutual empowerment towards a shared goal and where human feedback becomes a crucial driver for CPSoS adaptivity. TEACHING addresses the challenge by integrating AI with fundamental concepts of security and dependability stemming from the AI-human-CPSoS interactions, and by considering their impact on the underlying computing system. TEACHING develops a human-aware CPSoS for autonomous safety-critical applications, based on a distributed, energy-efficient and dependable AI, leveraging edge computing platforms integrating specialized computing fabric for AI and in-silico support for intelligent cybersecurity. The goal is to design a computing software and system supporting the development and deployment of adaptive and dependable CPSoS applications, allowing to exploit a sustainable human feedback to drive, optimize and personalize the provisioning of the offered services. TEACHING outcomes will fundamentally impact the development of autonomous safetycritical systems, providing means to improve their safety, dependability and overall acceptability. This impact will be demonstrated by TEACHING in two pilots concerning autonomous driving and aviation. More Information

FLAMENCO - Forward Looking Approaches for Green Mobility Ecosystem Network Collaboration

The project FLAMENCO (Forward Looking Approaches for Green Mobility Ecosystem Network Collaboration) goal is to analyse and pilot forward looking approaches and methods to enable and make sustainable the collaboration on the skills intelligence in the Automotive-Mobility Ecosystem. It is the direct support of the Pact for Skills large-scale partnership implementation in the Automotive-Mobility Ecosystem - Automotive Skills Alliance. The challenge is to make the collaboration of the partnership pragmatic and sustainable (outreach to other Pact for Skills partnerships as a good practice) so that it brings valuable info about the new technological and societal trends, related skills needs training offer/needs and other goals in terms of the skills intelligence leading up to the re-/up-skilling within the European mobility ecosystem. The project main activities will be to analyse the sector in cooperation with stakeholders in terms of the needs, tools, requirements and goals of the sectoral collaboration on skills intelligence via different methods, such as desk research, survey or workshop all validated by the sectoral stakeholders. Finding will be implemented in the methodology, methods and models for the collaboration and unified methodology and approach will be provided and further tested and piloted on individual focus groups. Project will develop recommendations and good practices in form of case studies and will provide them alongside with tested, frequently updated and validated methods which are to be rolled-out in different Pact for Skills partnerships and sustained after the project ends. All of this is supported by strong partnership with background and experience with skills agenda, pioneering Pact for Skills partnership as a full partner, strategical projects and implementation of such activities. Dissemination will assure that the impact of the project is consistent and on the desired level to the all Pact for Skills community in Europe. More information.

FWF - DENISE - Doctoral School for Dependable Electronic-Based Systems

Electronics-based systems (EBS) are becoming more and more prevalent in production, infrastructure and transport, but are only accepted if people trust these systems. Reliability is therefore becoming the cornerstone for the social acceptance of electronics-based systems. The researchers in the doctoral programme Dependable ElectroNIc-Based SystEms (DENISE) will explore concepts, methods and application-oriented tools to make EBS more reliable. The project deepens the very good relationship between FH Joanneum and Graz University of Technology through a joint doctoral programme. DENISE creates an integrated research framework across disciplinary boundaries and links reliability concepts of sensors with networked embedded devices. Existing strengths will be built upon and by pooling complementary expertise DENISE will lead to sustainable progress in the EBS sector. More information

OPEVA - OPtimization of Electric Vehicle Autonomy

The project OPEVA aims for innovation on aggregating information from the vehicle, not only from the battery but also from other internal sensors and behaviours, to create a model of performance and consumption specific to the individual vehicle and its driver (TD1). It aims to optimize the individual driving episode using the out-vehicle data such as state of the road, weather, charging station location and occupancy etc. that are collated from the back-end systems (TD2). OPEVA will further address the challenges associated with the communication between the vehicle and the infrastructure to gather data from the back-end systems (TD3). It aims for innovation in the use of recharging stations and related applications (TD4). It further aims to achieve better understanding on what the battery and its constituent cells are really doing during real world use for an improved battery management system (TD5). Finally, TD6 covers the driver-oriented human factors for optimizing the electrical vehicle usage. The TDs from the most deeply embedded in the vehicle to its support in the cloud, which need to interwork in an optimal fashion to deliver in one decade a better level of systemic optimisation for personal mobility that took ten decades to achieve with fossil fuels. On the other hand, economic factors (N-TD1), legal and ethical aspects (N-TD2), EV related development by the human (N-TD3), and societal and environmental factors (N-TD4) will be taken into consideration in the OPEVA methods for a higher acceptance and the awareness of the society regarding the these developments. More information.

OSCAR - Optimized System for a Collaborative Approach of mobile Robots

The requirements for autonomous mobile robots in a warehouse are increasing with the high growth of digitalisation in the industry. In this context, it is of enormous importance to also advance the development of mobile robots, also known as shuttles. As an example, the efficiency in the processing of tasks can be mentioned here. In order to achieve this increase in efficiency, a certain intelligence must be introduced among the shuttles or in a swarm of any size. The range for this intelligence is broad and various aspects can be considered. More Information

Reconfigurable Processor Architectures

Multi-core hardware and software is becoming increasingly important in embedded automotive systems (EAS). While a large amount of complex algorithms, sensors, and actuators demand for more computational power, the desired integration density and real-time requirements of modern electronic control units (ECU) often necessitate truly parallel code execution. In addition, networked smart cars will require future embedded automotive software to be flexibly composed of a varying set of functions and services in order to retain the long-term interoperability of vehicles among each other. This project aims on researching the foundations and practical application of novel operating systems concepts and processor architectures for dynamically composed embedded multi-core systems with hard real-time constraints. Programming paradigms and schedulability analysis at kernel and application level is thus equally important as hardware support for connecting and isolating tasks and cores. More Information

SPiDR - Secure, Performant, Dependable, and Resilient Wireless Mesh Networks

SPiDR brings together the latest advances in wireless networking, localization, benchmarking, collaborative awareness, and machine learning, towards the development of secure, resilient, and highly-performant wireless mesh networks. Within SPiDR, we will create benchmarking infrastructures supporting experimentation on wireless networks based on Wi-Fi, Bluetooth Low Energy (BLE), and Ultra-wideband (UWB) technology; we will design dependable and scalable networking protocols that are resilient to malicious agents; we will provide autonomous entities such as drones with RF context- and location-awareness, as well as with the ability to identify and mitigate security threats, network anomalies, and coexistence issues. More Information

TRANSACT - Transform safety-critical cyber-physical systems into distributed solutions for end-users and partners

The overarching goal of TRANSACT is to develop a universal distributed solution architecture for the transformation of safety-critical cyber-physical systems from local, stand-alone systems into safe and secure distributed solutions. More Information

TWIN-SOLUTION - Digital Twin Enabled Commissioning and Testing of Failsafe Automation

The goal of this project is the development of new methods development, test and deployment tools supported by digital twins in order to substantially reduce engineering overheads and to simplify the production of future automation systems. More Information