D1.5. Acceptance cartography of video-based AAL applications

This deliverable presents an “acceptance cartography” for video-based Ambient Assisted Living (AAL) technologies, mapping the factors that influence whether people accept or reject these systems. It explores how artificial intelligence (AI) supports AAL tools, particularly video-based ones used for monitoring and supporting older adults and people with disabilities at home. While these technologies can improve safety and independence, their acceptance depends on various conditions. Key influences include perceived usefulness, ease of use, trust in the technology, and privacy concerns. The report stresses that acceptance is not a simple yes/no decision but a complex process shaped by personal, technological, and contextual factors. It highlights the importance of users’ previous experiences with care, their technical confidence, living situation, and health status. Privacy concerns are especially significant, as many people are uncomfortable with constant video monitoring, particularly in private areas. Trust and transparency about how data is collected and used are essential. The report concludes with best-practice recommendations, including providing user control over the system, ensuring transparency, and offering flexible, privacy-sensitive design options to support user confidence and uptake.