Akteure
86 Einträge
Eintragsliste
OrganisationNewsadoo
Newsadoo (Linz) betreibt eine KI-gestützte Nachrichtenplattform, die Inhalte automatisch sammelt, mittels künstlicher Intelligenz versteht und sortiert und sie personalisiert sowie themenspezifisch zugänglich macht. Der personalisierte Newsfeed wird laufend anhand des Leseverhalt
LinzMedien & AV- Organisation
Robotic Eyes
Develops XR solutions for construction industry
ArchitekturQuerschnitt 
OrganisationStoryclash
Storyclash (Linz) betreibt eine KI-Plattform für Creator- und Influencer-Intelligence im Marketing. Die KI durchsucht Millionen von Content-Beiträgen, identifiziert passende Creator, deckt Marken- und Wettbewerbssignale auf und filtert nach Glaubwürdigkeit, Compliance und Offenle
LinzMedien & AV- Organisation
Reactive Reality
Developing platforms for AR/VR experiences
FashionGaming & XR - Forschung
BIMReason: Validating BIM model correctness
Forschungsarbeit zu einem Framework für die automatisierte Konformitätsprüfung von BIM-Gebäudemodellen mittels semantischem Reasoning auf IFC-Daten.
Aktiv: Dezember 2024Architektur - Forschung
A Natural Language Parameter Catalogue for Algorithm-Aided Design of Modular Housing
Forschungsarbeit, die für den algorithmusgestützten Entwurf modularer Wohnbauten einen Parameterkatalog in natürlicher Sprache entwickelt — Anwendungsfall: mehrgeschoßiger Wohnbau in Wien.
Aktiv: Juli 2024Architektur - Forschung
Integrating Digital Twins with BIM for Enhanced Building Control Strategies: A Systematic Literature Review Focusing on Daylight and Artificial Lighting Systems
Systematische Literaturübersicht zur Verbindung digitaler Zwillinge mit BIM für Gebäudesteuerung, mit Fokus auf kombinierte Tageslicht- und Kunstlichtsteuerung.
Aktiv: März 2024Architektur - Forschung
Integrating BIM-LCA to Enhance Sustainability Assessments of Constructions
Forschungsarbeit zur Integration von BIM und Ökobilanzierung (LCA) für schnellere und genauere Umweltbewertung von Bauvorhaben — untersucht am Zusammenspiel von Revit und OneClick LCA.
Aktiv: Jänner 2024Architektur - Forschung
The Binaural Rendering Toolbox. A Virtual Laboratory for Reproducible Research in Psychoacoustics
The Binaural Rendering Toolbox (BRT) is a set of software libraries, applications, and definitions aimed as a virtual laboratory for psychoacoustic experimentation.The BRT is developed in the framework of the SONICOM project 1 and will include the algorithms developed in the 3D Tune-In Toolkit 2 in a new open, extensible architecture.At the core of the BRT Toolbox, a library provides C++ implementations of listener models, source models, and environment models, including a growing collection of portings to different audio frameworks such as PureData, MaxMSP and VST plugins, by means of the Avendish library.In addition, the BRT also includes an application controlled via the Open Sound Control (OSC) protocol.This paper describes the architecture of the BRT, its main features, and its application to reproducible psychoacoustics experiments.The toolbox provides a complete trace of the experiment, including the delivered binaural audio, annotated with the listener and source movements.For this purpose, a new SOFA convention is proposed to store dynamic measurements, facilitating their use in the Auditory Model Toolbox (AMT).
Aktiv: Jänner 2024Medien & AV - Forschung
Digital Technologies and Material Passports for Circularity in Buildings: An In-Depth Analysis of Current Practices and Emerging Trends
Abstract The construction industry is undergoing a significant transformation driven by digitalization and an unwavering commitment to implementing circular economy (CE) principles and sustainability into its core practices. Emerging digital technologies (DTs), such as Material Passports (MPs), Building Information Modelling (BIM) Artificial Intelligence (AI) and Scanning technologies, Blockchain technology (BCT), the Internet of Things (IoT) stand out as pivotal tools capable of expediting the transition towards CE implementation in buildings. This study highlights the significant potential of six DTs to support CE application throughout the building lifecycle. Furthermore, it delves into the potential synergies among these diverse DTs, highlighting the additional benefits that collaboration can bring across different lifecycle stages of a building project. Particular emphasis is placed on the integration of MPs with other DTs, showing promise in assessing resource availability, volumes, and flows. This integration optimizes waste reduction and recycling plans, contributing to more precise selective and smart deconstruction planning. The combined use of DTs offers substantial benefits to stakeholders, enabling them to make informed decisions regarding maintenance and understand the current quality of specific materials. Through these means, the study aims to provide a comprehensive overview of the array of DTs propelling circular building practices. It also explores emerging trends in this dynamic field, scrutinizing the effectiveness of adopting these technologies throughout the building life cycle stages, and anticipating potential challenges these technologies may face.
Aktiv: Jänner 2024Architektur - Forschung
Automation of escape route analysis for BIM-based building code checking
Forschungsarbeit zur halbautomatischen Fluchtweganalyse für die BIM-basierte Bauordnungsprüfung, validiert an realen Gebäudemodellen in Solibri Office.
Aktiv: September 2023Architektur - Forschung
Using deep learning to generate design spaces for architecture
We present an early prototype of a design system that uses Deep Learning methodology—Conditional Variational Autoencoders (CVAE)—to arrive at custom design spaces that can be interactively explored using semantic labels. Our work is closely tied to principles of parametric design. We use parametric models to create the dataset needed to train the neural network, thus tackling the problem of lacking 3D datasets needed for deep learning. We propose that the CVAE functions as a parametric tool in itself: The solution space is larger and more diverse than the combined solution spaces of all parametric models used for training. We showcase multiple methods on how this solution space can be navigated and explored, supporting explorations such as object morphing, object addition, and rudimentary 3D style transfer. As a test case, we implemented some examples of the geometric taxonomy of “Operative Design” by Di Mari and Yoo.
Aktiv: März 2023Architektur - Forschung
Deep learning’s shallow gains: a comparative evaluation of algorithms for automatic music generation
Abstract Deep learning methods are recognised as state-of-the-art for many applications of machine learning. Recently, deep learning methods have emerged as a solution to the task of automatic music generation (AMG) using symbolic tokens in a target style, but their superiority over non-deep learning methods has not been demonstrated. Here, we conduct a listening study to comparatively evaluate several music generation systems along six musical dimensions: stylistic success, aesthetic pleasure, repetition or self-reference, melody, harmony, and rhythm. A range of models, both deep learning algorithms and other methods, are used to generate 30-s excerpts in the style of Classical string quartets and classical piano improvisations. Fifty participants with relatively high musical knowledge rate unlabelled samples of computer-generated and human-composed excerpts for the six musical dimensions. We use non-parametric Bayesian hypothesis testing to interpret the results, allowing the possibility of finding meaningful non -differences between systems’ performance. We find that the strongest deep learning method, a reimplemented version of Music Transformer, has equivalent performance to a non-deep learning method, MAIA Markov, demonstrating that to date, deep learning does not outperform other methods for AMG. We also find there still remains a significant gap between any algorithmic method and human-composed excerpts.
Aktiv: März 2023Medien & AV - Forschung
AI Diffusion as Design Vocabulary - Investigating the use of AI image generation in early architectural design and education
This paper investigates the potential of Text-to-Image AI in assisting the ideation phase in architectural design and education. The study proposes a structured workflow and tests it with first-year architecture students. It aims to create a comprehensive design vocabulary by using AI-generated images as primary design references and incorporating them into a modelling workflow. The paper implements a process combining specific vocabulary extraction, image generation, 2D to 3D translation, and spatial composition within a six weeklong design course. The findings suggest that such a process can enhance the ideation phase by generating new and diverse design inspirations, improve spatial understanding through the exploration of various design elements, and provide students with a targeted visual vocabulary that helps define design intention and streamlines the modelling process.
Aktiv: Jänner 2023Architektur