Structural Health Monitoring (SHM) requires reliable spatial data to support the assessment of infrastructure conditions and potential geometric inconsistencies. Recent advances in mobile and low-cost geospatial technologies, including LiDAR-equipped smartphones and handheld SLAM-based systems, have enabled rapid and flexible point cloud acquisition, although their achievable accuracy in operational scenarios remains a key question. This study presents a comparative analysis of point clouds acquired using an iPhone 15 Pro Max equipped with a viDoc RTK Rover and a Leica BLK2GO same spatial LiDAR system, against a terrestrial laser scanning (TLS) reference dataset collected with a Leica RTC360. All datasets were georeferenced within a common GNSS-based reference framework using RTK corrections and ground control points measured with a Leica GS15 receiver. The comparison focuses on the geometric agreement between datasets through cloud-to-cloud distance analysis and the evaluation o fverticalandhorizontalpointclouddifferences.Statisticalindicatorsderivedfromopen-sourceprocessingenvironmentsareusedtocharacterizethespatialconsistencyofthemobileacquisitionswithrespecttothereferencemodel.Theresultshighlightthepotentialofbothsmartphone-basedandSLAM-basedLiDARsystemsforrapid,first-levelinfrastructureinspections,particularlyincontextswherefastdataacquisition,easeofuse,andopen-sourceworkflowsareprioritizedoverhigh-precisiondeformationmonitoring.Thestudyprovidespracticalinsightsintotheadvantagesandlimitationsoflow-costandmobileLiDARtechnologiesforoperationalSHMapplications.
Comparative Analysis of Point Clouds Acquired by iPhone 15 Pro Max Equipped with viDoc RTK Rover and Leica BLK2GO for Structural Condition Assessment
Pascucci, N.
;Marconi, L.;Alicandro, M.;Dominici, D.;Zollini, S.
2026-01-01
Abstract
Structural Health Monitoring (SHM) requires reliable spatial data to support the assessment of infrastructure conditions and potential geometric inconsistencies. Recent advances in mobile and low-cost geospatial technologies, including LiDAR-equipped smartphones and handheld SLAM-based systems, have enabled rapid and flexible point cloud acquisition, although their achievable accuracy in operational scenarios remains a key question. This study presents a comparative analysis of point clouds acquired using an iPhone 15 Pro Max equipped with a viDoc RTK Rover and a Leica BLK2GO same spatial LiDAR system, against a terrestrial laser scanning (TLS) reference dataset collected with a Leica RTC360. All datasets were georeferenced within a common GNSS-based reference framework using RTK corrections and ground control points measured with a Leica GS15 receiver. The comparison focuses on the geometric agreement between datasets through cloud-to-cloud distance analysis and the evaluation o fverticalandhorizontalpointclouddifferences.Statisticalindicatorsderivedfromopen-sourceprocessingenvironmentsareusedtocharacterizethespatialconsistencyofthemobileacquisitionswithrespecttothereferencemodel.Theresultshighlightthepotentialofbothsmartphone-basedandSLAM-basedLiDARsystemsforrapid,first-levelinfrastructureinspections,particularlyincontextswherefastdataacquisition,easeofuse,andopen-sourceworkflowsareprioritizedoverhigh-precisiondeformationmonitoring.Thestudyprovidespracticalinsightsintotheadvantagesandlimitationsoflow-costandmobileLiDARtechnologiesforoperationalSHMapplications.Pubblicazioni consigliate
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