<?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/322eef060d6640678eb73de75c3df5e3&quot; frameborder=&quot;0&quot; width=&quot;1148&quot; height=&quot;861&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>861</height><width>1148</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>861</thumbnail_height><thumbnail_width>1148</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/322eef060d6640678eb73de75c3df5e3-b1864cdf698e007d.gif</thumbnail_url><duration>86.696</duration><title>Building Safer Routes with Police and Lighting Data</title><description>This Loom explains how SafeVogue addresses unsafe routing by integrating safety data into maps. The speaker notes that in 1 in 3 Indian women feel unsafe walking alone at night in Toronto, and that maps often show the fastest route but not the safest route because safety data is trapped in government portals and not connected to police and streetlight information. They describe indexing 34,000 police crime records and 160,000 streetlight locations, scoring routes in under two seconds. The resulting safety API sits on top of Google Maps to help users choose routes that reflect safety.</description></oembed>