Ensuring Reliability in Consumer LiDAR-Based Spatial Compliance: A Scan Quality Validation Framework for Regulated Residential Care Environments

Abstract

Consumer-grade LiDAR sensors, particularly those embedded in mobile devices, have demonstrated sufficient accuracy for many building measurement applications under controlled conditions. However, deployment in regulatory compliance contexts introduces a reliability problem that accuracy specifications alone cannot address: when operated by untrained or semi-trained personnel across heterogeneous residential environments, measurement uncertainty expands substantially and non-uniformly. This paper characterizes the distribution-of-quality problem in consumer LiDAR deployment for Home and Community-Based Services (HCBS) facility compliance under 42 CFR 441.301 and the ADA 2010 Standards for Accessible Design, and presents the Scan Quality Validation Layer (SQVL) — a seven-component pre-processing framework designed to make scan-derived compliance findings defensible in regulatory and legal contexts. The SQVL evaluates point density, surface coverage completeness, SLAM drift, level transition integrity, doorway capture quality, lighting artifacts, and occlusion gaps before any geometry extraction or compliance rule evaluation occurs. Findings are classified by an accuracy band taxonomy that stratifies compliance rules according to their spatial measurement requirements, determining whether consumer LiDAR is sufficient, insufficient, or conditionally sufficient for each rule category. A mandatory hybrid verification workflow is triggered for all precision-dimension rules and all threshold-adjacent measurements. The proposed framework draws design principles from quality assurance practices in autonomous vehicle perception systems and medical imaging device qualification. Proposed thresholds are design estimates grounded in instrument specifications and the SLAM literature; empirical calibration across facility environments is the subject of a forthcoming validation study. This work defines a methodological foundation for spatially defensible compliance assessment using accessible scanning hardware.