{"id":685,"date":"2015-07-08T07:57:51","date_gmt":"2015-07-08T07:57:51","guid":{"rendered":"https:\/\/mccoymart.com\/post\/?p=685"},"modified":"2022-11-16T15:16:02","modified_gmt":"2022-11-16T09:46:02","slug":"faro-releases-pointsense-for-revit","status":"publish","type":"post","link":"https:\/\/mccoymart.com\/post\/faro-releases-pointsense-for-revit\/","title":{"rendered":"FARO Releases PointSense for Revit\u00ae"},"content":{"rendered":"<p>FARO, one of the world\u2019s most trusted source for 3D measurement, imaging, and realization technologies, announced the release of the newly designed PointSense for Autodesk\u2019s Revit\u00aebuilding design software. PointSense introduces breakthrough functionality to significantly improve the evaluation and conversion of point cloud data to Building Information Modeling (BIM). BIM has become a standard in the planning, building and management of new facilities and Autodesk Revit\u00ae is one of the most established BIM programs for the Architecture, Engineering and Construction (AEC) industry. FARO\u2019s latest software release accelerates and simplifies the analysis and design of laser scan data directly in Autodesk Revit\u00ae. PointSense is FARO\u2019s first software release following their recent acquisition of kubit\u2122 . Jay Freeland, FARO\u2019s President and CEO stated that as BIM continues to be an established requirement in the construction industry, they recognize the need to provide customers with a complete field-to-finish solution. \u201cPointSense enhances the architectural design process by simplifying the extraction of BIM models to point clouds. This is merely the beginning of FARO\u2019s efforts to greatly enhance scan-to-BIM workflows,\u201d he added.<\/p>\n<p>PointSense users will experience additional functionality compared to traditional native Autodesk Revit\u00ae tools previously available in the market. Some of the new features include: extraction and alignment of architectural walls, creation of Revit\u00ae family types such as <a href=\"https:\/\/mccoymart.com\/product\/doors\/\">doors<\/a>, windows, beams, construction lines and ground models, real 3D snap-to-point clouds, plane detection and scaled ortho-image generation. PointSense will be available to users beginning 4 May 2015. For more information on PointSense for Revit\u00ae, please visit:<\/p>\n","protected":false},"excerpt":{"rendered":"<p>FARO, one of the world\u2019s most trusted source for 3D measurement, imaging, and realization technologies, announced the release of the newly designed PointSense for Autodesk\u2019s Revit\u00aebuilding design software. PointSense introduces breakthrough functionality to significantly improve the evaluation and conversion of point cloud data to Building Information Modeling (BIM). BIM has become a standard in the &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/mccoymart.com\/post\/faro-releases-pointsense-for-revit\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;FARO Releases PointSense for Revit\u00ae&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":686,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_links_to":"","_links_to_target":""},"categories":[18],"tags":[751],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v19.10 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>FARO Releases PointSense for Revit\u00ae | McCoy Mart<\/title>\n<meta name=\"robots\" content=\"noindex, nofollow\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"FARO Releases PointSense for Revit\u00ae | McCoy Mart\" \/>\n<meta property=\"og:description\" content=\"FARO, one of the world\u2019s most trusted source for 3D measurement, imaging, and realization technologies, announced the release of the newly designed PointSense for Autodesk\u2019s Revit\u00aebuilding design software. PointSense introduces breakthrough functionality to significantly improve the evaluation and conversion of point cloud data to Building Information Modeling (BIM). 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