Research Projects
There are 28 results.
m-hub - a web-based data hub for collection and query of material compositions of the building stock of the City of Vienna
The project creates a web-based platform with which the material composition of buildings within the city of Vienna can be entered and queried. In the background, a prediction model based on artificial intelligence is trained to make forecasts for buildings that have not yet been cataloged.
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.
MokiG: Monitoring for climate-neutral buildings
The aim is to develop and implement an innovative monitoring concept to demonstrate the achievement of climate neutrality in buildings. A central element here is the integration and linking of various data sources. The basis for this is a data mesh structure, artificial intelligence and the creation of digital twins. Finally, the methodology will be tested on real buildings and discussed with users.
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.
Urban Sky - Satellite-based planning and analysis applications for climate-neutral and resilient cities
The project investigates how satellite data can support cities and municipalities (e.g. urban development, spatial energy planning, mobility transition). Based on demand and potential analyses, service concepts will be derived that integrate existing data and tools with satellite applications. The results will be presented in a study and a Space4Cities implementation roadmap.
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.
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.
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.
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.
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.
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.
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.
TOPS – Topology-optimised reinforced concrete slabs with digital formwork and reinforcement
The TOPS project is investigating material-efficient ribbed concrete slabs, which save up to 50% of the concrete used in conventional flat slabs by topology-optimisation. A 'file-to-factory' process enables the automated production of formwork and reinforcement using digital technologies. The construction method reduces CO₂ emissions and contributes to the decarbonisation of the construction industry.
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.
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.
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.
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.
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.
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.
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.