Ethical Design of Holography with Dense wireless Networks

Introduction

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.

Project Overview

HOLDEN proposes a radically new approach to perception by concisely analyzing 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.

Social Aspects of RF-Sensing

For the first time ever, HOLDEN constitutes a concentrated effort to explore social aspects of RF-sensing to guide technological advance and to derive technology for ethically and privacy-compliant perception. Central to HOLDEN is the development of ethical and privacy constraints.

Development of Concepts

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 multi-target recognition and ubiquitous perception with unprecedented accuracy. This constitutes a radical paradigm shift from a technology-centric perspective to a privacy-centric one via privacy by design.

Research Paths

HOLDEN achieves this goal along three high-risk, complementary, and privacy-centric paths:

1. Path 1: Continuous-space measurement points: Radio-based 3D vision by holographic image processing of RF wave-fronts.
2. Path 2: Discrete-space measurement points: Advanced 3D beamforming for human-scale recognition and tracking through dense massive connected antenna arrays.
3. Path 3: Signal processing and learning: High-dimensional tensor processing for the distinction of complex activities and motion from massive-dimensional RF data.

Benchmarking and Application

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.