Research Projects
There are 28 results.
BIM.sustAIn - Artificial Intelligence to enhance sustainability in BIM projects
The construction sector faces growing challenges in meeting sustainability requirements, particularly during early project phases where key decisions on materials, construction methods, and energy concepts are made. This project aims to leverage AI and BIM to optimize sustainability assessments by providing precise CO₂ balance forecasts and material suggestions. The innovative approach reduces manual effort and supports the implementation of climate-neutral construction, contributing significantly to Austria’s climate goals.
Climbing plant NAVI - Webapplication for the reliable selection of climbing plants
The comprehensive web application "Climbing Plants NAVI" takes important parameters such as the type of greening, weight classes, toxicity, ecological value, the possibility of culinary use, into account and thereby supports the selection of suitable climbing plants for greening projects. The climbing plants NAVI is not only intended for municipal representatives, planners and other professionals, but is also directed at private individuals.
Circular Bio Floor- Floor construction made from biomaterials
In this project biogenic building materials from wood industry waste and geopolymer binders are developed that can be used as tamped fill or 3D-printed dry-screed elements in timber construction. These materials offer functional benefits and an excellent eco-balance, contribute to the conservation of forests and enable the production of separable and reusable floor segment panels using digital manufacturing technologies. That significantly reduces the consumption of primary raw materials.
Autology - the automated ontology generator
Ontologies form the basis for the acquisition, analysis/processing, utilization, documentation, and archiving of building and component data throughout all stages of the lifecycle. Currently, the semantic description and structuring of data can only be achieved with significant manual effort. At this point, the Autology project utilizes Artificial Intelligence. The overarching project objective is the automated extraction and generation of metadata for the creation of ontologies from the building automation system, employing innovative AI-based approaches.
DataScience4SmartQuarters - Energy saving potentials through neighbourhood and community planning – Part 2
DataScience4SmartQuarters develops and researches an innovative method for the fast and efficient evaluation of simulation scenarios (building/energy, mobility) for communities.
TEA-PUMP – Techno-economic Analysis of Thermoelectric Modules for Efficiency and Performance Enhancement in Heat Pumps for Residential Buildings
The TEA-Pump project explores the innovative use of thermoelectric elements (TEM) in compression heat pumps to enhance their efficiency and performance. Through a comprehensive techno-economic analysis, promising heat pump (HP) configurations for use in urban multi-family housing are identified. The project makes a significant contribution to the decarbonization of heating and cooling supply and supports the development of climate-neutral cities through energy-efficient, future-oriented heat pump technologies.
ThermEcoFlow: Innovative technologies and methods for indoor air comfort and energy optimisation in thermal spa buildings
ThermEcoFlow aims to optimize the energy consumption of thermal spas facilities through improved simulation models and AI-supported control systems. By precisely modelling airflow, humidity loads, and evaporation, combined with AI-driven regulation, the project seeks to reduce energy consumption and CO₂ emissions in the long term while enhancing indoor comfort for visitors.
SPOT – Smart Parking Space Optimization Tool
SPOT develops a data-driven tool for demand-oriented optimization of parking spaces in urban areas to use space more efficiently and promote climate neutrality. The tool supports cities in reducing parking areas and creating green spaces by calculating evidence-based parking space ratios.
IMPACT – Hybrid hydraulic and electric charging of stratified compact hot water
The IMPACT project is developing an innovative decentralised hot water storage technology for large-volume urban housing. Thanks to a novel, flat design, the system enables highly efficient utilisation of renewable energy sources such as heat pumps and photovoltaics. The aim is to create a cost-efficient, sustainable solution for decarbonising water heating that is optimised using intelligent energy management and machine learning methods.
Kimoni – Artificial Intelligence for Monitoring the Performance of Green Infrastructure
Kimoni develops an AI-based tool for high-resolution analysis and assessment of Green Infrastructure for climate change adaptation. By combining satellite and geospatial data with machine learning, Kimoni provides a cost-efficient and scalable solution to comply with the EU Taxonomy and optimize climate-friendly investments.
iLESS - Intelligent load profile analysis to maximize self-consumption of solar power
The goal is to reconstruct the individual contributions of various devices from existing load profile curves. This problem is of fundamental importance in the context of maximizing self-consumption of solar power by private households.
SIMPLE AD Evaluator - S.I.M.P.L.E. Sustainable Integration Modeling and Predictive Leveraging Evaluator
The SIMPLE AD Evaluator fills an existing gap in sustainable local planning by providing a low-threshold and collaborative evaluation tool for early planning phases. By linking questionnaires with System Dynamics models, the tool delivers well-founded decision-making foundations and customized sustainability checklists. This supports municipalities, project developers, and decision-makers in achieving a strategic and cost-efficient sustainable transformation from concept to implementation.
SAGE - scalable multi-agent architectures for facility management and energy efficiency
The SAGE project is developing scalable multi-agent architectures that enable buildings to recognize operational anomalies autonomously and react dynamically to environmental changes. The integration of multi-agent architectures in combination with Large Language Models (LLMs) and the development of a human-in-the-loop approach will optimize the collaboration between humans and machines. These solutions should significantly reduce the energy consumption of buildings and increase user-friendliness.
ReSpace – Reclaiming Spaces
ReSpace is developing an AI-based model for identifying, categorizing, and activating sealed areas. Existing data sources (aerial and satellite images, mobile network data, land registry entries) are integrated and enhanced with dynamic analysis to derive evidence-based recommendations for action.
SELF²B - self-aware, self-diagnosing buildings, HVAC, and PV systems for the next generation of energy efficient operations
SELF²B develops and demonstrates an AI-based, self-learning, and self-diagnosing fault detection and diagnosis (FDD) solution for HVAC and PV systems in two buildings in Vienna. The innovation surpasses the current state of the art by combining semantic data, ontologies, and machine learning. The goal is to achieve energy savings and efficiency improvements in building operations and to make the technology widely applicable.
cityclimAIte - Study on AI applications to achieve and support climate-neutral cities
The central task of this study is to provide decision-makers with a comprehensive overview and to derive recommendations for the efficient use and benefits of AI based on the estimated effects. The aim is to strengthen national value chain in this field of technology through appropriate, supportive framework conditions.
AI4FM - Artificial Intelligence for Facility Management
AI-based anomaly and fault detection in buildings. Digital twins of buildings with simulation models for testing and optimizing rule-based fault detection methods. Mining of the recorded time-series data from existing Building Management Systems to train Machine Learning models for fault detection.
BOSS - Building Energy Systems on causal reasoning
The project develops novel Causal AI methods for automated fault detection in buildings. It aims to derive semantic structures from time series data and transparently model cause-effect relationships. This provides the foundation for scalable, explainable FDD solutions to reduce energy consumption and emissions in the building sector.
GreenGEO - Data-based integration of climate change adaptation measures into spatial planning
Green and blue infrastructure (GBI) is a key instrument in the fight against climate change. Nevertheless, deciding where and in what form it should be used most effectively remains a challenge in spatial planning practice. The development of a digital model that links location-specific climate risk data with suitable GBI measure proposals will make this much easier and more objective.
Green BIM 3 - Tools for Standardised Data Integration of BIM and Digital Twins, Including Ecosystem Services
The project aims to enhance the availability and integration of BIM data, ecological parameters, and other relevant information into the workflows of the green sector. To achieve this, a web-based application with suitable interfaces will be developed. The foundation for this is a detailed requirement specification, which will be established through interviews, workshops, and research, linking the individual components of the application.