<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/9f95b29db0344b58bbf266be55a5b028&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/9f95b29db0344b58bbf266be55a5b028-7de56dafb8d149ac.gif</thumbnail_url><duration>300.203</duration><title>Detecting Column Locations and Heights in BitSense Using AI Technology</title><description>In this video, I demonstrate how our Outglot Engineering system detects the location and heights of columns in a BitSense project, specifically using the Onionta transit station as an example. I walk you through the process of scanning structural plans to identify steel columns and their heights, highlighting that the system uses AI and is stochastic, meaning results can vary. I found 19 columns on the foundation plan and 10 on the second floor framing plan, with heights ranging from 13 to 27 feet. I encourage you to visit our website at www.outglot.engineering to explore more about our technology and try out the demo projects. Your feedback on the system&apos;s performance is invaluable as we continue to refine our approach.</description></oembed>