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.
The digitization efforts of the last decades have led to automated data collection, which presents many companies with major challenges in data processing and analysis. RISC Software GmbH relies on smart technologies in the field of data engineering and artificial intelligence (AI) to analyze (real-time) information and collected data pools from texts, images or sensor data and derive suitable optimization measures. It supports companies in efficiently processing and analyzing their data.
Data Engineering as a solid basis for the efficient use of Data Science
Before analysis, data from various sources is integrated and made usable efficiently. Data engineering is thus a prerequisite for the efficient use of data science, especially in the Big Data area. Central activities such as data cleansing, data integration, data model transformation, improvement of data utilization through fast queries and data preparation are supported by AI..
Analysis of data and images
Mathematical processes and methods from the fields of visual analytics, data analysis and machine learning enable an analysis of structured data and images (machine vision or computer vision). In the process, correlations and patterns are recognized, which can be used for error and cause analysis as well as for continuous quality monitoring.
Processing and interpretation of text data
Natural Language Processing can also be used to automatically process (unstructured) text data and act as an interface between humans and machines. For example, documents can be automatically assigned to previously defined categories, important information can be extracted from texts, or the mood of customers can be recognized.
RISC Software GmbH meets the current requirements of modern data management and offers an individually customizable tool for automated knowledge extraction from data, texts and images. Start with Industrial AI and benefit from a better understanding of your data.
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.
SEE-KID – Software Engineering Environment for Knowledge-based Interactive Eye Motility Diagnostics
The SEE-KID / CEVD research initiative has been working on the computer-aided simulation of eye malpositions and their surgical correction for more than 20 years.
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.
From development to product maturity with Docker
RISC Software GmbH supported the LKR Leichtmetallkompetenzzentrum Ranshofen in rolling out a software product for production in continuous aluminum casting. In order to unite different user environments and versions, the Docker platform was used.
Forschungsprojekt TRAPH: Traffic Management and Information System
TRAPH aimed to design and prototype the data management of ASFiNAG’s new traffic management and information system 2.0.
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.
Project RESINET: RESIlience enhancement in energy NETworks
The RESINET project addresses the issue of resilience of energy grids, taking into account the change in framework conditions from centralized, unidirectional systems to grids with a significantly higher share of renewable, fluctuating energy feeders (“prosumers”), increasing storage capacities in the grid interconnection and controllable loads.
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.
Contact us
Error: Contact form not found.