LiDArgus: Accommodating Diverse Privacy Preferences in LiDAR Sensing Through Configurable Sub-Zoning

Abstract

LiDAR sensors are increasingly being adopted in smart home environments to enable user activity recognition for a wide range of applications, including resident safety monitoring, health tracking, and behavior modeling. While the advantages of LiDAR-based activity recognition are well recognized, supporting diverse privacy preferences remains an ongoing challenge. Different user groups often have competing needs: homeowners may favor high-resolution sensing for health monitoring, whereas guests may prefer lower-resolution sensing or even temporary deactivation of the system. To navigate these varied requirements, we introduce a spatially adaptive approach that divides the LiDAR sensing field into configurable sub-zones, each with adjustable sensing capabilities, sizes, and locations. This design empowers users to personalize sensing settings according to their individual privacy preferences. We demonstrate the feasibility of this approach through a proof-of-concept prototype and assess its effectiveness via two user studies. Our findings offer insights to inform the design of privacy-aware LiDAR sensing systems in smart environments.