Projects
There are 42 results.
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.
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.
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.
KityVR - Artificial intelligence techniques to implement CityGML models and VR visualization
The goal of the project is to link 3D city models and virtual reality for energy-relevant applications as key-enabler for digital planning, construction and operational management. Missing data will be calculated using statistical enrichment methods.
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.
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.
OctoAI: The next generation of high-performance edge AI for smart buildings
Current IoT (Internet of Things) solutions for buildings depend almost exclusively on cloud infrastructure and cloud-based services. In the OctoAI project, we are developing the next generation of high-performance Edge AI (Artificial Intelligence) for smart buildings. In OctoAI, we combine the concept of edge AI with user-centric energy services and test two edge-ready applications.
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.
ReCon: Development of a resilient hook-and-loop-fastening-system for the adaptable assembly of building components in the building industry
Systemic examination of the hook-and-loop fastener and building component interfaces for the development of a resilient fastening system between parts/components with different functions and lifespan. The desired result serves to verify the fastening system and forms a basis for further research and establishment in the building industry.
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.
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.
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.
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.
TWIN - Digital twins for sustainable buildings
Digital building twins have hardly been used in practice due to an often unfavourable cost-benefit ratio. The aim of the TWIN project is to bring together use cases of digital building twins with a high ecological and economic impact in order to prepare application scenarios with great implementation potential.
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.
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.
VR4UrbanDev - Virtual Reality as an innovative, digital tool for the integrative urban development of the future
Virtual reality (VR) has the potential to make complex issues more quickly comprehensible and directly tangible. In the VR4UrbanDev project, we are using this potential for energy planning processes for buildings and urban districts. On the basis of test areas, we develop methods for importing and visualising energy-related real-time data and simulation data in the VR environment.
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.
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.
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.