[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-650781-105":3,"detail-sidebar-cat-0-en-105":80,"doc-detail-650781-en":130},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":73,"head_meta":75,"extra_data":77,"updated_unix":79},105,"en","mobile-3d-lidar-based-scan2bim-process-a-comparison-of-point-cloud-processing-tools","Mobile 3D LiDAR-based Scan2BIM Process - A comparison of point cloud processing tools","","Mobile 3D LiDAR scanning is explored as an accessible, cost-effective alternative for data acquisition in Scan2BIM workflows, addressing the complexity and expense that often block successful implementation. The study transforms mobile LiDAR point clouds from a simple workspace in a historical school building into parametric, semantically rich BIM elements. It compares point cloud processing tools by accuracy, compatibility of data formats, and capacity for component generation, situating results within HBIM. Findings show efficient conversion from 3D point clouds to BIM objects via multiple software tools.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/mobile-3d-lidar-based-scan2bim-process-a-comparison-of-point-cloud-processing-tools/650781/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/mobile-3d-lidar-based-scan2bim-process-a-comparison-of-point-cloud-processing-tools/650781.png","ImageObject",300,407,{"name":42,"@type":43},"Himbo","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-28","2026-10-24",true,{"@type":52,"interactionType":53,"userInteractionCount":30},"InteractionCounter",{"@type":54},"ViewAction",{"@type":56,"mainEntity":57},"FAQPage",[58,64,68],{"name":59,"@type":60,"acceptedAnswer":61},"Why is data acquisition a barrier in Scan2BIM workflows, and how does mobile 3D LiDAR address it?","Question",{"text":62,"@type":63},"Data acquisition is complex and costly in Scan2BIM workflows, which hinders implementation. Mobile 3D LiDAR scanning provides a more accessible, easy-to-implement, and cost-effective way to capture point cloud data.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"What is the study’s main goal for the collected point cloud data?",{"text":67,"@type":63},"The study aims to convert mobile 3D LiDAR point cloud data into Building Information Modeling (BIM) workflows, producing parametric and semantically rich BIM elements for architectural documentation and cultural heritage preservation.",{"name":69,"@type":60,"acceptedAnswer":70},"How do the authors evaluate point cloud processing tools?",{"text":71,"@type":63},"The evaluation focuses on accuracy, data format compatibility, and the tools’ capacity for generating components, supporting comparisons for BIM object creation in the mobile scanning pipeline.","https://schema.org",{"og:url":32,"og:type":74,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":76,"canonical":32},"index,follow",{"doc_id":78,"site_id":7},650781,1792898563,{"code":4,"msg":81,"data":82},"success",[83,87,91,95,100,105,110,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":84,"show_sort_weight":85,"slug":86},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":88,"show_sort_weight":89,"slug":90},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":92,"show_sort_weight":93,"slug":94},"Exam",70,"exam",{"id":96,"doc_module":4,"doc_module_name":25,"category_name":97,"show_sort_weight":98,"slug":99},5,"Comic",60,"comic",{"id":101,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},6,"Technology",50,"technology",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":107,"show_sort_weight":108,"slug":109},7,"Healthcare",40,"healthcare",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":112,"slug":113},8,30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":96,"slug":129},19,"General","general",{"code":4,"msg":81,"data":131},{"doc_id":78,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":111,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":30,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":123,"language":139,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":12,"update_tm":143,"read_time":144},687197100911,"https://ap-avatar.wpscdn.com/avatar/a000239b6f1da00475?x-image-process=image/resize,m_fixed,w_180,h_180&k=1785132997149421697","Mobile 3D LiDAR-based Scan2BIM Process:  \nA comparison of point cloud processing tools  \nHandanAş Çemrek1, Seda Sönmez2, ÜmitIşıkdağ3  \n1,2,3 Mimar Sinan Fine Arts University  \n1,2{20242109002\\[20242109001}@ogr.msgsu.edu.tr](20242109001}@ogr.msgsu.edu.tr3 umit)[3](20242109001}@ogr.msgsu.edu.tr3 umit)[ umit](20242109001}@ogr.msgsu.edu.tr3 umit).ısı[kdag@msgsu.edu.tr](kdag@msgsu.edu.tr)[ ](kdag@msgsu.edu.tr)The data acquisition process has been both a key issue and a strong barrier in the success of Scan2BIM workflows, due to its complex (hard to implement) and costly nature. Today technologies such as mobile 3D LiDAR scanning, provides both easy to implement and cost-effective alternative for data acquisition. This study explores the transformation of point cloud data of a simple workspace in an historical school building acquired through mobile 3D LiDAR scanning into Building Information Modeling (BIM) workflows, with a particular focus on generation of object-based semantically rich digital models for architectural documentation and cultural heritage preservation. The study explores how data collected through mobile devices with 3D LiDAR capabilities can be transformed into parametric and semantically rich BIM elements (objects). In this context a comparative analysis of well-known point cloud processing tools was conducted, focusing on accuracy, data format compatibility and component generation capacity. The study situates its findings within the broader framework of HBIM, highlighting how mobile scanning technologies can enhance semantic modeling and support dynamic, data-rich representations of assets. The results emphasize that the mobile 3D LiDAR scanning is an accessible, cost-effective, and efficient data acquisition alternative in Scan2BIM workflows and the acquired 3D point cloud data can efficiently be converted into BIM objects using multiple software tools.  \nKeywords: BIM, 3D Lidar, Point Cloud, Scan2BIM, Object-Based Modeling,  \nDigitalization, Mobile Laser Scanning, Digital Twin, Cultural Heritage, HBIM.  \nINTRODUCTION  \nToday, Digital Twin applications and Building Information Modeling (BIM) play a critical role in digitally documenting both construction industry and cultural heritage. In this context, point cloud data serves as a key interface and optimizing data captured via mobile devices comes to the fore. RGBD sensors and SLAM (Simultaneous Localization and Mapping) algorithms on mobile devices enhance environmental perception these devices and facilitate the integration of LIDAR technology into Digital Twin and HBIM processes.  \nStudy explores the integration of 3D LiDAR scan data captured using an iPad Pro with Scaniverse app into BIM workflows. The data was exported in LAS format, processed in PointCaband converted into parametric model elements in Revit. The study aims to assess the potential of mobile-based scanning for BIM integration and the interactions between different software tools.  \nBACKGROUND RESEARCH  \nIn recent years, mobile LiDAR technologies have become widespread as a low-cost and portable  \nVolume 1 – Confluence – eCAADe 43 | 503  \ndocumentation tool. Cultural heritage documentation, in particular, benefits from the rapid data collection capabilities of mobile scanning devices (Akbaylar et al., 2024) . Compared to traditional fixed laser scanners, mobile LiDAR systems offer significant advantages in terms of speed and ease of use. Handheld scanners, smartphone LiDAR’s and drone-assisted scanning have diversified this technology (Qu and Sun, 2015) .  \nIn this process, RGBD sensors and SLAM algorithms increase the 3D mapping capabilities of mobile devices, enabling detailed documentation of cultural heritage. RGBD sensors provide color image (RGB) and depth data at the same time, allowing realistic spatial models to be created. SLAM algorithms track the location of the device, ensuring precise data alignment and point cloud creation (Kim et al., 2020) .  \nHBIM and IFC format integratio","cbCain0L2q6NNyIV","https://ap.wps.com/l/cbCain0L2q6NNyIV","pdf",684805,"English","# Introduction\n# Background Research\n## Digital Documentation of Cultural Heritage with Mobile LiDAR\n# Comparative Tool Evaluation","[{\"question\":\"Why is data acquisition a barrier in Scan2BIM workflows, and how does mobile 3D LiDAR address it?\",\"answer\":\"Data acquisition is complex and costly in Scan2BIM workflows, which hinders implementation. Mobile 3D LiDAR scanning provides a more accessible, easy-to-implement, and cost-effective way to capture point cloud data.\"},{\"question\":\"What is the study’s main goal for the collected point cloud data?\",\"answer\":\"The study aims to convert mobile 3D LiDAR point cloud data into Building Information Modeling (BIM) workflows, producing parametric and semantically rich BIM elements for architectural documentation and cultural heritage preservation.\"},{\"question\":\"How do the authors evaluate point cloud processing tools?\",\"answer\":\"The evaluation focuses on accuracy, data format compatibility, and the tools’ capacity for generating components, supporting comparisons for BIM object creation in the mobile scanning pipeline.\"}]","Mobile 3D LiDAR-based Scan2BIM Process - A comparison of point cloud processing tools | PDF",1792844202,25]