Suchergebnisse für "Factsheet: Energietechnologien gestalten, die für alle sinnvoll und nutzbar sind"
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.
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.
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.
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.
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.
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.
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.
Circular Bio Floor- Floor construction made from biomaterials
In this project biogenic building materials from wood industry waste and geopolymer binders are developed that can be used as tamped fill or 3D-printed dry-screed elements in timber construction. These materials offer functional benefits and an excellent eco-balance, contribute to the conservation of forests and enable the production of separable and reusable floor segment panels using digital manufacturing technologies. That significantly reduces the consumption of primary raw materials.
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.
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.
BIMstocks - Digital Urban Mining Platform: Assessing the material composition of building stocks through coupling of BIM to GIS
The main goal of BIMstocks is the development of a method for the digital capturing of the material composition of the existing building stock for follow up modelling of an Urban Mining Platform as well as for the prediction of the recycling potentials.
BATTMON - Increasing the usable charging capacity, service life and safety of battery storage systems in urban areas
The aim of BATTMON is to develop an improved method of determining the condition of battery storage systems for applications in buildings and neighborhoods. To this end, area-based foil sensors are being developed for the spatially resolved measurement of temperature and pressure. This data will be used to estimate the state of charge and also the state of health more accurately and to detect cell damage at an early stage in order to reduce the risk of fire and explosion.
3D*3B - 3D-Concret Printing, Reinforcement for low carbon and bending stressed structures.
The project is about 3D printed structural elements and their integration in building structures. The focus is predominantly set on bending stresses structural elements like panels and slabs. Results will point out technical, logistic and climate relevant aspects.
M-DAB - Digitise, analyse and sustainably manage the city's material resources
The research project investigates how digital technologies can support us in determining the existing and future material resources in construction qualitatively (building materials and their recycling) and quantitatively (quantities of building materials).
BIMpeco - Environmentally relevant product data in collaborative BIM environments
Construction products can pose a risk to the environment and health due to their pollutant content or releases. In the BIMpeco project, workflows and data structures for digital information management of this environmentally relevant product data are developed. For this purpose, the new ISO standards ISO 23387 and ISO 19650-1 are tested and synchronized with established process flows. The project results will be made available on an open-source basis and can be integrated into any Common Data Environment (CDE) that complies with the standards mentioned. The BIMpeco project is the first to lay the foundations for product information management of environmentally relevant properties in the CDE, covering the entire lifecycle and supply chain.
BIM2BEM Flow - Continuous BIM-based energy efficient planning
Automated integration and assignment of exchange requirements between the design and simulation programs, based on the elaborated exchange information requirements, should enable continuous energy efficiency planning along the design phase.
Green BIM - Green building infrastructure as part of BIM-based planning and maintenance
Fusion of greenery and BIM planning to achieve a friction-free conducting and maintenance. By analysing the case studies, “Green BIM” examined to what extent typical steps in planning regarding greened buildings can be edited by characteristic software programs in a BIM-equitable way. The expected outcomes are supplements to international standards for data structures in civil engineering (IFC / ISO 16739) which are further on added to BIM applications by the software industry.
digiactiv - digital transformation for more interactivity in MEP-(mechanical, electrical and plumbing-)planning
The aim of the digiactiv project is to improve the interoperability between the different stakeholders in the building construction sector using open and neutral semantic data models. With digital transformation processes, digiactiv helps to increase the quality of planning and the operation of buildings, as well as to minimize the interface risk between various stakeholders.
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.