Suchergebnisse
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.
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.
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.
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.
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.
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.
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.
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.
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.
Vitality City - Holistic energy strategies for cities in transition
Energy simulation of any size city (municipalities) based on the data from laser scanning and satellite analysis (Geodata) to obtain dynamical energy demands and available energy resources.
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.
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.
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.
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.