{"version":"1.0","provider_name":"FactoryLab","provider_url":"https:\/\/factorylab.fr\/en\/","author_name":"Cassandra Fontaine","author_url":"https:\/\/factorylab.fr\/en\/author\/cassandrafontaine\/","title":"PRECINET: Internal cleanliness inspection of piping | FactoryLab","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"8S8lmaSlR4\"><a href=\"https:\/\/factorylab.fr\/en\/precinet-internal-cleanliness-inspection-of-piping\/\">PRECINET: Internal cleanliness inspection of piping<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/factorylab.fr\/en\/precinet-internal-cleanliness-inspection-of-piping\/embed\/#?secret=8S8lmaSlR4\" width=\"600\" height=\"338\" title=\"&#8220;PRECINET: Internal cleanliness inspection of piping&#8221; &#8212; FactoryLab\" data-secret=\"8S8lmaSlR4\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/factorylab.fr\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","thumbnail_url":"https:\/\/factorylab.fr\/wp-content\/uploads\/2025\/04\/Image-PRECINET.png","thumbnail_width":590,"thumbnail_height":443,"description":"The PRECINET feasibility study is aimed at testing the approach of using artificial intelligence to detect pollution (grease and loose parts) in industrial piping, along with the possibility of incorporating AI into a video endoscope available in the market."}