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
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
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
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
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
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
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
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.
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
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.
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
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 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
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
The European Commission has set an ambitious goal to double the share of electronic component design and production done in Europe by 2030. As one significant contribution to achieve this goal, academic and industrial stakeholders focus on developing and expanding an open-source RISC-V ecosystem as a strategic investment for Europe. The industry-initiated TRISTAN project aims to extend, expand, and industrialise the European RISC-V ecosystem to compete with existing commercial alternatives. The project aims to leverage the Open-Source community to increase productivity and quality. In addition, the broad-based international consortium will expose a large number of engineers to RISC-V technology, which will further promote adoption and ensure that this ecosystem becomes a sovereign European alternative to existing industrial standards. The national consortium in Austria is making a significant contribution to TRISTAN, contributing to the ambition to establish Austria as “chip forge” in Europe. The diversity of the partners and their complementary position in the value chain ensure a strong Austrian footprint in TRISTAN and a high impact with regard to dissemination and exploitation. Furthermore, with the intensive cooperation between academic and industrial partners, the open-source aspects are brought into focus just as much as the exploitation interests of the industrial partners. TUG will focus on the development of HW/SW co-design solutions (with industrial partners) for RISC-V ISA custom extensions. TUG will provide solutions from the investigation of the ISA extension through simulation and design space exploration analysis targeting performance, timing and energy use optimizations. More information.
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