Document Type

Conference Proceeding

Publication Date

Summer 5-14-2026

Abstract

This paper analyzes how capture parameters affect indoor mobile LiDAR scan fitness for-purpose for BIM-based facilities management. Despite extensive research on geometric accuracy and automated modelling performance, limited work has systematically examined how acquisition conditions influence the practical usability of raw scans for BIM/FM applications. A controlled experimental investigation used an Apple iPhone 16 Pro's integrated LiDAR sensor to capture 36 indoor scans under twelve factorial combinations of scan speed, illumination level, and motion pattern. Each condition was repeated three times. Usability was assessed using several components,Fco a gate-based pass/fail criterion, enclosure geometry, openings, ceiling services, and geometric clarity using a structured five-point ordinal rubric. Five domain experts independently evaluated a selection of scans to validate the reliability of the rubric then inter rater reliability was assessed using Krippendorff's alpha. The usability instrument was supported by satisfactory to robust inter-rater reliability for primary geometric dimensions. Usability scores and gate pass rates increased with slower scan speeds and higher lighting levels; however motion pattern did not affect usability scores. SLAM-based reconstruction exhibited stochastic tendencies with significant scan-to-scan variability found in repeated captures under identical conditions. The study demonstrated that on-device abstraction is unreliable beyond basic enclosure representation, highlighting the requirement for raw point cloud assessment before processing. Acquisition conditions greatly affect scan practicality, regardless of geometric accuracy requirements. This study established an expert-validated usability framework and empirically identified condition-sensitive capture methods for spatial generalization, geometric precision evaluation, and downstream BIM/FM workflow comparison.

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