Suchergebnisse
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.
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.
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.
AFOM - Automatic failure and optimisation analysis by data-acquisition
In the project, methods will be developed for analysing measured value curves to detect changes in operation or failures in the system. By integrating BIM data of buildings, corresponding models will be generated to validate the heating, ventilation, and air conditioning (HVAC)-networks, which will be used for analysis.
mAIntenance - Investigation of AI supported maintenance and energy management
Optimized & reliable operation of Heating, Ventilation and Air Conditioning (HVAC) systems in terms of maintenance and energy management, using predictive, data-based & self-learning error detection. Conceptual design and prototype implementation of an AI (Artificial Intelligence) tool for automated data analysis and recommendations for technical building operators.
Circular Twin - A Digital Ecosystem for the Generation and Evaluation of Circular Digital Twins
By 2030, more than the equivalent of two Earths will be needed to meet the demand for natural resources, therefore a transition to circular systems is essential, especially in the construction industry. The digital "Circular Twin" ecosystem enables the early implementation of circular economy goals as well as end-to-end digitalization in construction utilizing Digital Twins, Generative Design Algorithms and Virtual Reality.
AIA4ALL - development of open, modular and automatable employer’s information requirements (EIR) and BIM execution plan (BEP)
The Employer's Information Requirements - EIR (German: AIA) - serves the client to define goals and use cases for a BIM-based construction project. The aim of this project is to create a modular, machine-readable AIA that can be seamlessly integrated into the tool landscape of openBIM projects. This is done by developing an open platform for creating use cases for the AIA.