NextBase: Intelligent adaptation of production and intralogistics systems
The aim of the project is to enable the use of methods from prescriptive analytics & machine learning in our automation projects.
Artificial intelligence (AI) is being applied in a wide variety of areas, for example in business, industry or healthcare. It can be used to solve complex tasks that were previously unsolved. For example, AI-based systems are able to recognize patterns and correlations or make predictions for the future. AI-based systems have great potential to relieve or supplement human resources. In particular, the combination of humans and machines can increase efficiency and effectiveness.
Machine Learning and Deep Learning
Machine learning (ML) is a subfield of AI that enables machines to learn from data. ML models are able, for example, to recognize patterns and correlations or to make predictions for the future based on data.
Deep learning (DL), in turn, is a subfield of machine learning in which deep neural networks are used to learn complex relationships. Deep neural networks are characterized by a high number of learnable parameters. These parameters can solve difficult tasks, but require a large amount of training data and special algorithms.
How can you benefit from AI?
You also benefit from artificial intelligence: AI systems enable the automation of complex (decision-making) processes, in some cases with an accuracy superior to human expertise. By drawing on the latest findings from AI research, RISC Software GmbH can achieve robust solutions for your individual use cases in the shortest possible time.
The foundation for successful AI models is appropriate data collection. As an AI enabler, RISC Software GmbH’s strength is to prepare this data appropriately and to make AI systems usable for the end user in daily applications. In doing so, RISC Software GmbH draws on its many years of experience in a wide variety of application domains (logistics, industry, medicine). As a research institution, it has a very good overview of the state of the art and is able to transfer the latest methods and findings into applicable systems.
RISC Software GmbH supports you with expertise and experience in the implementation of your individual AI use cases. Great emphasis is placed on quality and sustainability. The development and implementation of the AI systems are based on ethics, transparency and fairness, whereby the systems not only work efficiently and effectively, but are also responsible and reliable.
Reference projects
DiTwin: Revolutionizing road management with digital twin technology
DiTwin revolutionizes road management with digital twin technology for optimized asset management.
Research project AIMS
The aim of AIMS is to develop and validate an early warning system using artificial intelligence to warn of deteriorating conditions on the hospital ward before they occur.
Project News-Extracted Evolving European Datasphere (NEEED)
In the FFG-funded research project NEEED, researchers and developers from RISC Software GmbH, SCCH GmbH and Newsadoo GmbH worked together to expand the Newsadoo technology to include an evolutionary graph of local, national and international news events.
Project MUST
The main objectives of the MUST project are to directly and indirectly influence mobility behavior in terms of climate and environmentally friendly traffic management through traffic avoidance, modal shift and traffic improvement. For example, the aim is to test which combinations of information can be used to transport traffic information across target groups in order to achieve positive effects.
SafeRoadWorks:Safe highway construction sites
The FFG-funded project “SafeRoadWorks” primarily aims to increase safety on highway construction sites for both drivers and workers.
FLOWgoesS2T – Automated, AI-based integration of voice messages in the editorial workflow of a traffic newsroom
In the FFG-funded research project FLOWgoesS2T, researchers and developers from XEBRIS Solutions GmbH, aiconix GmbH and RISC Software GmbH worked together to analyze telephone voice messages on Austrian traffic events.
Virtual Aneurysm: Simulation, Training and Assessment of Neurosurgical Interventions
Simulator for training clipping operations
EndoPredictor – Prediction system for complications after endovascular aortic repair based on geometric-biomechanical data
Artificial intelligence for predicting complications in aortic aneurysm treatments.
Act4Whistleblowing- Trustworthy whistleblowing system
In the AWS-funded research project “Act4Whistleblowing”, researchers and developers from RISC Software GmbH dealt with the automated processing of textual information from the whistleblowing system of Compliance2b GmbH.
Platform-ZERO aims to reach zero defect manufacturing for the photovoltaic industry
Das EU-Projekt “Platform-ZERO” zielt darauf ab, die allgemeine Produktionsqualität von Photovoltaikgeräten zu verbessern und gleichzeitig die Herstellungskosten durch eine Null-Fehler-Fertigung zu senken.
EU project metaFacturing: Digitalization in metal part production
The EU-funded Horizon Europe project MetaFacturing aims to advance digitization in the field of metal part production – casting and welding.
Surface 3D
Inaccurate estimates of burn size can lead to suboptimal medical decisions with significant consequences for patients. With the help of Surface 3D, a precise calculation of the burn size is made possible, thus ensuring patient safety and supporting medical staff in everyday clinical practice.
Medical Image Processing, Modeling and Simulation based on Artificial Intelligence
The research area “Medical Image Processing, Modeling and Simulation based on Artificial Intelligence” (MIMAS.ai) covers a cross-section of highly dynamic research topics, which are becoming increasingly important in medical application fields, not least due to current technological advances.
MEDUSA – Medical EDUcation in Surgical Aneurysm clipping
The aim of the MEDUSA consortium is to develop a revolutionary training and planning platform for neurosurgeons in order to simulate complex brain interventions in a detailed and holistic manner.
MC3 – Medical Cognitive Computing Center
The State of Upper Austria sees artificial intelligence (AI) as one of the most important technology trends of the next decade and is therefore creating the new Medical Cognitive Computing Center (MC3), a center to research and implement optimal patient care through the use of novel methods in the field of artificial intelligence.
Project opt1mus
The opt1mus project is developing a holistic system for the light metals industry that will use digital twins and artificial intelligence to make production more efficient and lower emissions.
Research project BurnCase 3D
One research focus of the Department of Medical Informatics is medical modeling and simulation, which includes in particular research in the field of objective diagnosis and documentation based on virtual patients (three-dimensional models adapted to real patients).
Research Project nARvibrain: Improved brain tumour diagnosis and treatment
The nARvibrain project (“Augmented Reality supported Functional Brain Mapping for Navigated Surgery Preparation and Education”) aims to improve brain tumor diagnosis and treatment, increase patients’ awareness and understanding of the disease, and enhance the quality of medical education by combining modern Artificial Intelligence (AI) and eXtended Reality (XR) methods.