HOLDEN - Ethical Design of Holography with Dense wireless Networks
UT Project leader: prof.dr. Ciano Aydin
UT Project members: dr. Sage Cammers-Goodwin, dr. Nolen Gertz, dr. Michael Nagenborg
duration: 01-06-2023 till 31-05-2026
Summary:
Ubiquitous perception, by sensing of objects, subjects and gestures, is a pivotal challenge for future technology: it enables personalized services such as smart living, automated logistics or interaction through free-space gestures. However, it also challenges ethical and moral boundaries and threatens privacy. HOLDEN proposes a radically new approach to perception by concisely analysing ethical constraints and privacy risks while re-thinking RF-based sensing. We establish necessary conditions for privacy preserving and ethically compliant sensing and develop new paradigms respecting these constraints.
For the first time ever, HOLDEN constitutes a concentrated effort to explore social aspects of RF-sensing to guide the technological advance and to derive technology for ethically and privacy compliant perception. Central to HOLDEN is the development of ethical and privacy constraints. We use these findings to derive privacy and ethically compliant concepts for RF-based perception. We will develop a system of distributed multi-antenna devices for simultaneous multitarget recognition and ubiquitous perception with unprecedented accuracy, which constitutes a radical paradigm shift from a technology-centric perspective to a privacy-centric one via privacy by design. HOLDEN achieves this goal along three high risk, complementary, and privacy-centric paths:
Path 1: Continuous-space measurement points: Radio-based 3D vision by holographic image processing of RF wavefronts.
Path 2: Discrete-space measurement points: Advanced 3D beamforming for human-scale recognition and tracking through dense massive connected antenna arrays.
Path 3: Signal processing and learning: High-dimensional tensor processing for the distinction of complex activities and motion from massive-dimensional RF data. The resulting breakthrough approaches and algorithms will be compared against application-level benchmarks via usage scenarios in the fields of logistics, smart living, and free-space.
