Overview
The IDN Carte Blanche Project aims at preparing and submitting the research proposal within the Swiss-Polish Cooperation Programme, Research and Innovation Programme (Call 2025). The consortium consists of academic partners: HSLU, Lodz University of Technology and companies: Giant Lazer, gutundgut, Locomot.
The main project aims to design, develop, and validate a modular, no-code digital platform that integrates Augmented Reality (AR) and Artificial Intelligence (AI) to support the creation and delivery of immersive cultural and tourism experiences. The main objective is to empower non-technical users— tour guides, museum staff, and cultural animators—to independently build AR applications for mobile devices, tailored to specific sites and audiences.
The platform will synergies with an AI engine to support content creators in generating rich multimedia materials—such as spoken narratives, summaries, AI-driven image animation, and illustrative content—without specialized technical skills. Key features include text-to-speech, text-to-image, AI-based summarization, enabling fast and flexible content creation for immersive experiences. The system will incorporate localization technologies—including SLAM and QR codes —to ensure precise spatial anchoring of digital content within real-world environments.
The project will be co-designed and piloted in collaboration with two cultural and tourism organizations— a Polish and Swiss one. The research approach will be based on mixed methods, including literature reviews, stakeholder interviews, participatory design workshops, and iterative prototyping. Two pilot implementations will be conducted, each engaging approx. 120 end-users, to evaluate usability, accessibility, and cultural relevance.
A key focus is accessibility. By leveraging AI to adapt format, language, and complexity, the platform will support inclusive experiences for users with cognitive, sensory, and physical impairments. The entire system will be developed according to high usability and adaptability standards, enabling scalability across cultural and technological contexts.
The project aims to raise the solution’s from TRL2 to TRL7, paving the way for its practical deployment beyond the project’s scope.
