Suchergebnisse
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.
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.
Twin2Share - Digital twins for energy optimization in energy communities (ECs)
Digital twins to support energy communities over their life cycle. The project focuses on optimizing energy efficiency and costs, dynamic load management and the integration of users to promote sustainable energy use and the stabilization of the electricity grid.
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.
GeoDatKlim - Geo Data and Satellite Data for Carbon Neutral Cities
The Vienna Geospace Hub innovation lab will help optimize the application of geospatial and satellite data to solve complex urban challenges. The innovation lab serves as a networking platform for administration, science, economy, as well as a development and test environment for innovative use cases.
Topview - Methodology for the efficient use of remote sensing data for climate change adaptation and spatial energy planning
Development of integrated approaches to sustainable energy and heat planning in urban areas by utilising remote sensing data and geo-information-based technologies for decision-making in the planning of energy infrastructures and climate adaptation measures.
MaBo - material saving in bored piles - a contribution to reducing CO2-emissions in the construction industry
Development of an innovative method for saving material in bored piles in order to reduce CO2 emissions in the construction industry. By optimizing the construction methods and using alternative materials, the sustainability of the foundation bodies is to be improved.
QualitySysVillab - Protecting sustainable qualities in neighbourhood developments through process control and new digital methods
Development of a process concept to bring sustainable qualities in neighbourhood development from the intention and announcement level to the built reality. The process is supported by digital methods of energy and structural design and evaluated in the context of a case study.
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.
FlexHP - AI-supported control models for optimising the flexibility of heat pumps to reduce the load on the electricity grid
Development of a new type of energy management system for heat pumps that enables methods for intelligent heat pump operation and thus maximises flexibility. This requires forecast-based models for control that utilise technologies such as machine learning.
GreenFDT – Green Façade Digital Twin
In an interdisciplinary framework, the possibilities for optimizing the rear ventilation distance of façade greening elements and their potential impact on indoor and urban climate are being investigated. The precise and comprehensive investigation of these relationships is made possible by the extensive deployment of sensors and measuring tools and furthermore the development and integration of a digital twin in a BIM model.