The Joint Doctoral Programme in Interactive and Cognitive Environments offers PhD candidates an education programme in the field of research related to computer science, electronic and telecommunication engineering and industrial design. Candidates must hold a Master of Science (M.Sc.) degree or equivalent title and in-depth knowledge and understanding of the principles of ICT engineering. ICE aims at developing and enhancing master students’ knowledge and skills in order to shape a new generation of professionals able to exploit (and further enhance) cutting-edge ICT technologies to design and implement - in multi-disciplinary work teams - innovative solutions in the ever more pervasive fields of application. The programme has three major focuses, that will be iteratively pursued during the whole progress of the candidate’s track. The former concerns the acquisition and the formalization of knowledge in specific advanced domains, achieved through lectures and seminars. The second aims at keeping PhD students in strict touch with leading research groups that have proven experiences in research activities in basic disciplines necessary for the PhD course in the five partner universities. The latter involves actual industry/academy joint research activities on projects in cooperation with leading ICT companies, typically under international institutional umbrellas, such as the European Research Frameworks.

ICE Website

Eight partners - Univ. Paderborn (coordinator), Imperial College London, Univ. Oslo, Univ. Birmingham, EADS Munich, ETH Zurich, AIT Vienna and Klagenfurt University - will perform research on self-awareness in computing systems. The EPiCS project aims at laying the foundation for engineering the novel class of proprioceptive computing systems. Proprioceptive computing systems collect and maintain information about their state and progress, which enables self-awareness by reasoning about their behaviour, and self-expression by effectively and autonomously adapt their behaviour to changing conditions. The Pervasive Computing group will contribute research in the self-organization of visual sensor networks.

EPiCS Website

Mobi Trick is a joint research project together with Graz University of Technology and Efkon AG Graz. The goal is to develop a portable device for traffic enforcement (e.g., tolling). Mobile Systems are limited in size and resources. Therefore, there is not much space for a large number of sensors. Hence, the work in this project will focus on stereo vision but with two different types of cameras (e.g., color and infrared). The system needs to adapt itself to changing situations in case it is used at a new location. This requires adaptive calibration and online learning. Energy is always a scarce resoure in embedded devices. Thus the system must be designed to be very energy efficient. New approaches for context-aware dynamic power management will be explored.

Mobi Trick Website

The SRSnet project focuses on the design of a smart resource-aware multi-sensor network capable of autonomously detecting and localizing various events such as screams, animal noise, tracks of persons and more complex human behaviors. The project's research areas include (i) collaborative audio and video analysis, (ii) complex event detection and (iii) network reconfiguration. The SRSnet will be demonstrated in an environmental case study at the Hohe Tauern National Park.

This project is joint work with the Institute of Smart Systems Technologies at Klagenfurt University, the University of Udine and Lakeside Labs. It is funded by the European Interreg 4 Fund and the Carinthian Economic Promotion Fund.

SRSnet Website

The project Self-organizing Multimedia Architecture (SOMA) aims to capture the whole life-cycle of multimedia content in a single architecture for large distributed multimedia information systems.  In SOMA we focus on scenarios where events, which we understand as limited time periods of special importance, are a central concept. Within the project we investigate the behavior of small but efficient (computing) units working self contained but collaboratively.  A network of smart sensors reports events to a distribution network captured in multimedia data units.  In the distribution network events are analyzed, processed, stored, and prepared for delivery.  Events and related continuous data are either pushed to users on a subscription basis or consumed by users based on pull mechanisms.  Based on the consumption behavior and user feedback, popularity and relevance of delivered content is assessed and reported to the distribution and the sensor networks.SOMA is a joint research project of the Institute of Information Technology, the Institute of Networked and Embedded Systems as well as ASFiNAG Mautservice.

SOMA Website

McDAV Website

Microdrones are small-scale unmanned aerial vehicles carrying payloads such as cameras and sensors. This project develops a system for aerial sensing based on cooperating, wireless networked microdrones. Several microdrones will fly in formation over the area of interest in a selforganizing manner and deliver high-quality sensor data such as images or videos. These images are fused on the ground, analyzed in real-time, and delivered to the user. The project will perform original research in the areas (1) flight formation, (2) mission planning and control, and (3) sensor data interpretation, and it will demonstrate a collaborative microdrone system for fire response operations.

cDrones Website

Distributed smart cameras are real-time distributed embedded systems that perform computer vision using multiple cameras.  This new approach is emerging thanks to a confluence of demanding applications and the huge computational and communications abilities enabled by Moore’s Law.  This interdisciplinary field builds upon techniques from computer vision, distributed computing, and embedded computing and sensor networks. In this strategic research area we focus on several aspects of distributed smart cameras such as distributed resource management, collaborative image processing, sensor fusion and multimedia.  We develop prototypes of distributed smart camera systems and apply them in case studies such as traffic monitoring and security.

The world will witness a tremendous increase in the number of vehicles in the near future. Future traffic monitoring systems will therefore play an important role to improve the throughput and safety of roads. Current monitoring systems capture (usually vision-based) traffic data from a large sensory network; however, they require continuous human supervision which is extremely expensive.

In the EVis research project we investigate the scientific and technological foundations for future autonomous traffic monitoring systems. Autonomy is achieved by a novel combination of three approaches: First, vision-based detection and classification methods are augmented by self-learning and scene adaptation mechanisms which will significantly reduce the effort of manual configuration. Second, visual data is fused with data from other sensors such as radar, infrared or inductive loop sensors. Sensor fusion helps to improve the robustness and confidence, to extend the spatial and temporal coverage as well as to reduce the ambiguity and uncertainty of the processed sensor data. Finally, the developed vision and fusion methods are implemented on a distributed embedded platform which makes them wider applicable and supports real-time operation.

The technological output of the EVis project allows customers to take advantage of traffic management solutions that are easier to install, easier to operate and maintain, have a higher level of robustness. Furthermore, this technology enables multi-task operations in a single system capable of traffic monitoring, vehicle identification and classification, incident detection, traffic rule enforcement, and observation of (critical) driver's behavior.

The industrial partner EFKON is a globally acting company and expects EU, Middle East, North America, and Asia as primary markets for this technology. The midterm market potential is predicted as significantly over 100 million Euros.

EVis Website