Projects
There are 87 results.
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 KityVR project deals with key research aspects at the interface between 3D city models and virtual reality. It addresses questions such as how virtual reality can be used for visualization in the field of 3D city models and how machine learning and statistical methods can be used to enrich or complete energy-related data sets.
KliB40-Climate Compass: Climate-neutral Bregenz 2040, climate compass for the structured participation of stakeholders and the citizens
The "KliB40 Climate Compass" supports Bregenz on its path to climate neutrality by 2040 through transparent development, selection, and monitoring of measures. It facilitates the coordination of climate protection activities and actively involves stakeholders. By evaluating existing software solutions, the project ensures optimal digital support for planning and implementing the city's climate strategy.
LiveDetail - AI-Supported Structuring, Evaluation, and Generation of Construction Details
The exploratory project investigates the feasibility of an AI-supported workflow that can automatically identify, semantically structure, and convert technical planning details into an openBIM-/IFC-compatible format while also enriching them with ecological assessment indicators. Its objective is to enable planners and architects to access high-quality detail knowledge through intelligent, language-based interaction and thus support more sustainable and resource-efficient planning decisions in the construction industry.
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).
M-DAB2: Material intensity of inner development - resource assessment and localization of urban development potentials
For the first time, the material intensity of inner development (in terms of material quantities) for different design variants was considered in the evaluation of inner development potentials. A set of methods for the holistic evaluation of potential areas and different development variants and scenarios for resource-saving inner development was created.
MARGRET Bioshade - Building Physics-Based Quantification of the Shading and Cooling Performance of Building Greening
The MARGRET Bioshade project investigates the impact of building greening on energy efficiency, climate adaptation, and building assessment. Its focus is on quantifying the shading performance of vertical greening systems, analyzing the water balance and evaporative cooling effects of different greening solutions, and developing standardized parameters for planning, simulation, and technical guidelines.
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.
NEB Resources - Potentials in the Existing Urban Fabric for a Socially Inclusive, Circular and Climate-Just Matzleinsdorf
NEB Resources collaborates with residents to develop a feasible and politically supported transformation concept for a socially inclusive, circular, and climate-friendly Matzleinsdorf neighborhood in Vienna's Margareten district. Co-research, temporary interventions, and prototypes activate material and immaterial resources, thereby transforming physical spaces and social relationships.
NEXUS - AI for Next Generation Smart Buildings
he NEXUS project develops a novel AI-based framework for scalable fault detection and predictive maintenance of HVAC systems in buildings. NEXUS enables early fault detection without the need for large labeled datasets. The project aims to significantly reduce energy consumption, extend system lifetimes, and contribute to the decarbonization of the building sector.
National ‘governance matrix’ for the mapping and display, optimization, and funding of spatial and urban planning across institutions (BW STMX STB)
Development of an interactive governance matrix for the nationwide mapping, registration and optimization of programs and funding tools for spatial planning at every scale. By creating transparency as well as placing existing policies and governance tools in relation to one another, the matrix offers an overview across departments and institutions that allows synergies to be utilized and gaps to be closed.
NeoEAI4Control - Neuro-Symbolic Edge AI for Efficient and Robust Control in Energy Management
Increasing energy efficiency in buildings is a key goal of the energy transition, which, together with increasing digitalization, is leading to new requirements for intelligent control and regulation. Traditional control methods are reaching their limits. As part of the project, we propose the use of edge AI with specialized neuromorphic chips to enable scalable, decentralized, efficient, and real-time control in buildings.
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.
Q-Hub Villach - Climate neutrality and climate resilience as integral components of urban development instruments in Villach
The project aims to position the city of Villach as a model for systematic, climate-neutral and climate-resilient urban development by establishing the Q-Hub as a central hub between administration, research, business and civil society. This hub will develop methods, processes and standards and integrate them into urban planning instruments.
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.
Quartiershub Itzling - Innovation Lab for the Development of the Salzburg Itzling District Hub
Establishment of an urban district hub for coordinated, integrated, and socially inclusive neighborhood development and climate-responsive transformation. The development and close integration of an actors-, project-, data-, and knowledge-hub enables the piloting and evaluation of innovative, transferable solutions for integrated neighborhood development.
REHSA - Regenerative House for Health
REHSA focuses on the topic of "Demonstration of innovative building technologies and prototypes." The project will develop a groundbreaking, regenerative clinic model that goes far beyond conventional sustainability and combines innovative architecture, circular resource use, intelligent IT and medical technologies, and healing, people-centered environments.
RIGOR - Towards reproducible, transparent, and valid AI methods for buildings and cities
The RIGOR project investigates the actual added value and scientific reliability of AI-based methods in the context of buildings, districts, and cities. It focuses on reproducibility, transparency, and the objective comparison of modern AI approaches with simple, robust baseline models. The goal is to establish an evidence-based foundation for the responsible use of artificial intelligence in energy- and safety-critical applications in the built environment.
ReCapture - Rapid Capture and Precise Analysis of the Building Envelope as a Basis for Circular Economy in the Existing Building Stock
The goal of the study is to evaluate a novel sensor- and AI-based technology for automated detection, semantic segmentation, and 3D modeling of building envelopes.