EDGE-CARE: Trustworthy Edge AI for Privacy-Preserving RF Sensing in Future Care Technologies for Independent Living and Healthy Ageing

Dr Muhammad Zubair (PI), University of Leicester

Professor Qammer Abbasi (Academic collaborator), Centre for Integrated Sensing and Communication Enabling Cognitive Cities (ISAC3), University of Glasgow

Dr F. Farukh (Academic collaborator), De Montfort University

EDGE-CARE will explore how trustworthy, privacy-preserving sensing could support independent living and healthy ageing. Radio-frequency (RF) sensing can help detect occupancy, movement and activity without cameras or wearable devices. Edge AI processes sensing data locally on embedded devices, reducing reliance on cloud-based data transfer and offering opportunities to protect privacy.

Led by the University of Leicester, the project will investigate the trust, acceptability and practical adoption of these technologies in future care settings. Workshops, focus-group style discussions and knowledge exchange will bring together researchers, care technology practitioners, local authority stakeholders and relevant community participants. A simple demonstrator using commercially available radar will help participants explore sensing concepts and discuss privacy, transparency, reliability and the evidence needed for responsible deployment.

The demonstrator will support discussion and engagement; the project will not develop new AI models or deliver a clinically deployable care system. Findings will inform stakeholder-led recommendations, a practical framework for trustworthy adoption, a policy briefing and academic and public-facing dissemination. By connecting technical possibilities with the needs and expectations of people involved in care, EDGE-CARE aims to strengthen responsible innovation and establish a foundation for future interdisciplinary research and collaboration.

Impact: Planned engagement with a community and care technology stakeholder partner will bring practitioner perspectives on validation, deployment and adoption. Workshops and discussions will also involve relevant care, local authority and independent living stakeholders. Activities will seek inclusive participation through accessible and flexible formats, considering differing needs, experiences and levels of digital confidence.

EDGE-CARE aims to help researchers, practitioners and decision-makers understand the conditions under which Edge AI-enabled RF sensing could be trusted and accepted in care environments. The findings are expected to inform future design, validation and deployment discussions, with attention to privacy, dignity, accessibility and human-centred care.