
During three months on the aau-giraf/visual-tangible-artefacts repository, Morten Qvistgaard developed five core features spanning backend, frontend, and mobile domains. He built robust usage tracking infrastructure and user category analytics, leveraging C#, Entity Framework, and DTO patterns to stabilize data pipelines and enable personalized user experiences. Morten also delivered a caregiver dashboard with session management and dynamic user relationship APIs, integrating Dart and Flutter for responsive UI updates. In December, he implemented iOS webcam and audio support, updating Objective-C and Flutter configurations to enhance multimedia capabilities. His work demonstrated depth in API design, database modeling, and cross-platform integration.
Month 2025-12 - Repo: aau-giraf/visual-tangible-artefacts. Delivered iOS webcam and audio multimedia support, including project configuration updates for proper resource handling and updated iOS API URLs to enable multimedia features. This work enhances mobile user experience and lays the foundation for broader iOS media capabilities. Commit referenced: 8e24c7f4c28985150146d01e9fe2d24aa6f51b3c.
Month 2025-12 - Repo: aau-giraf/visual-tangible-artefacts. Delivered iOS webcam and audio multimedia support, including project configuration updates for proper resource handling and updated iOS API URLs to enable multimedia features. This work enhances mobile user experience and lays the foundation for broader iOS media capabilities. Commit referenced: 8e24c7f4c28985150146d01e9fe2d24aa6f51b3c.
November 2025 delivered two core platform enhancements for the aau-giraf/visual-tangible-artefacts project focused on caregiver workflow and user data access. Key backend and frontend changes enable caregivers to manage sessions end-to-end and provide dynamic access to user relationships, reducing manual data handling and enabling scalable analytics. The work lays the groundwork for improved caregiving experiences, session auditing, and more responsive UI across caregiver workflows.
November 2025 delivered two core platform enhancements for the aau-giraf/visual-tangible-artefacts project focused on caregiver workflow and user data access. Key backend and frontend changes enable caregivers to manage sessions end-to-end and provide dynamic access to user relationships, reducing manual data handling and enabling scalable analytics. The work lays the groundwork for improved caregiving experiences, session auditing, and more responsive UI across caregiver workflows.
October 2025 monthly summary for aau-giraf/visual-tangible-artefacts: Key features delivered include (1) Usage Tracking Infrastructure across ArtefactContext and UserContext with new fields and defaults to stabilize category usage data, adjust DTO conversion, and prevent nulls in the data pipeline; this improves analytics reliability and data quality. (2) User Category Usage Tracking and Display, exposing endpoints to retrieve a user's most-used categories ordered by usage count and last-used date, and updating the frontend to display and trigger usage tracking when a category is accessed. These features enable data-driven decisions and a more personalized user experience. Major bugs fixed include pipeline error fixes across multiple commits to stabilize the usage-tracking pipeline. Overall impact: end-to-end visibility into asset usage, improved data quality, and foundation for personalized UX and data-driven product decisions. Skills demonstrated: data modeling across ArtefactContext/UserContext; robust DTO handling and DB defaults; API design for usage endpoints; frontend-backend integration; auth edge-case handling; pipeline reliability and observability.
October 2025 monthly summary for aau-giraf/visual-tangible-artefacts: Key features delivered include (1) Usage Tracking Infrastructure across ArtefactContext and UserContext with new fields and defaults to stabilize category usage data, adjust DTO conversion, and prevent nulls in the data pipeline; this improves analytics reliability and data quality. (2) User Category Usage Tracking and Display, exposing endpoints to retrieve a user's most-used categories ordered by usage count and last-used date, and updating the frontend to display and trigger usage tracking when a category is accessed. These features enable data-driven decisions and a more personalized user experience. Major bugs fixed include pipeline error fixes across multiple commits to stabilize the usage-tracking pipeline. Overall impact: end-to-end visibility into asset usage, improved data quality, and foundation for personalized UX and data-driven product decisions. Skills demonstrated: data modeling across ArtefactContext/UserContext; robust DTO handling and DB defaults; API design for usage endpoints; frontend-backend integration; auth edge-case handling; pipeline reliability and observability.

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