Projects
In 2023, USTP – University of Applied Sciences St. Pölten's 126 research projects generated revenue of EUR 5.6 million. Interdisciplinary projects have grown in importance in recent years as a means to identify suitable answers to modern-day issues and devise appropriate solutions.
NITOB - Sustainable intermodal transport chains through optimization of rail operations
Investigates optimization approaches with regard to rail freight transport.
APOCRAT-ID
A legally compliant solution of a consent management platform for smart home systems.
IRS Cargo - Interoperability for ICT systems in rail freight transport.
Novel digital solutions improving the ways in which different systems in the railway sector communicate with each other.
OpenDALICC
An open source software framework for rights clearance in software- and data engineering.
DIRENE - Competences for the new era of user-driven digital innovation in rehabilitation
Addresses the need for furthering digital rehabilitation and the competences it requires
Evaluation of Motion Variability Using Portable Acceleration Sensors
An Examination of Human Gait Patterns with the Help of a Portable Measuring System (IMU)
GovMed – Governance of open data and digital platforms
Exploring ways in which the business activities of internet companies can be regulated.
Beyond Coding -Software Development of the Future
Making software developers familiar with key competences and upcoming key technologies for building and maintaining secure and resilient IT Systems.
Active deep learning for object detection
Developing novel strategies for integrating Active and Deep Learning for Artificial Intelligence
Plant Monitoring AI
Leveraging machine learning and predictive analytics for early detection of plant stress for the benefit of sustainability in farming
Scribe ID AI
Active Machine Learning for automatic identification of handwriting in 12th century manuscripts
IntelliGait 3D- Gait Data Mining
Establishing advanced analysis methods for modelling, classification and similarity retrieval of gait patterns to enable novel data-driven ways to access 3D gait databases