{"id":573,"date":"2025-05-12T10:15:57","date_gmt":"2025-05-12T08:15:57","guid":{"rendered":"https:\/\/websites.fraunhofer.de\/ki-fortschrittszentrum\/?post_type=projekt&#038;p=573"},"modified":"2025-09-04T10:47:42","modified_gmt":"2025-09-04T08:47:42","slug":"ki-supported-evaluation-of-3d-point-clouds-of-high-voltage-switchgear","status":"publish","type":"projekt","link":"https:\/\/www.ki-fortschrittszentrum.de\/en\/projekt\/ki-gestuetztes-bewerten-von-3d-punktwolken-von-hochspannungsschaltanlagen\/","title":{"rendered":"AI-supported evaluation of 3D point clouds of high-voltage switchgear"},"content":{"rendered":"<div class=\"wp-block-stackable-columns stk-block-columns stk-block stk-86663cd stk-block-background stk--has-background-overlay\" data-block-id=\"86663cd\"><style>.stk-86663cd {background-image:url(https:\/\/www.ki-fortschrittszentrum.de\/wp-content\/uploads\/2025\/05\/KI-Fortschrittszentrum_308_QC_Bewerten-von-3D-Punktwolken_Teaser.png) !important;min-height:520px !important;align-items:flex-end !important;padding-bottom:0px !important;margin-bottom:0px !important;display:flex !important;}<\/style><div class=\"stk-row stk-inner-blocks stk-block-content stk-content-align stk-86663cd-column\">\n<div class=\"wp-block-stackable-column stk-block-column stk-column stk-block stk-5a28863\" data-v=\"4\" data-block-id=\"5a28863\"><div class=\"stk-column-wrapper stk-block-column__content stk-container stk-5a28863-container stk--no-background stk--no-padding\"><div class=\"stk-block-content stk-inner-blocks stk-5a28863-inner-blocks\">\n<div class=\"wp-block-stackable-columns stk-block-columns stk-block stk-3e4895d\" data-block-id=\"3e4895d\"><div class=\"stk-row stk-inner-blocks stk-block-content stk-content-align stk-3e4895d-column\">\n<div class=\"wp-block-stackable-column stk-block-column stk-column stk-block stk-a094f1e\" data-v=\"4\" data-block-id=\"a094f1e\"><style>@media screen and (min-width:690px){.stk-a094f1e {flex:var(--stk-flex-grow, 1) 1 calc(30% - var(--stk-column-gap, 0px) * 2 \/ 3 ) !important;}}<\/style><div class=\"stk-column-wrapper stk-block-column__content stk-container stk-a094f1e-container stk--no-background stk--no-padding\"><div class=\"stk-block-content stk-inner-blocks stk-a094f1e-inner-blocks\"><\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-stackable-column stk-block-column stk-column stk-block stk-ba57710\" data-v=\"4\" data-block-id=\"ba57710\"><style>@media screen and (min-width:690px){.stk-ba57710 {flex:var(--stk-flex-grow, 1) 1 calc(30% - var(--stk-column-gap, 0px) * 2 \/ 3 ) !important;}}<\/style><div class=\"stk-column-wrapper stk-block-column__content stk-container stk-ba57710-container stk--no-background stk--no-padding\"><div class=\"stk-block-content stk-inner-blocks stk-ba57710-inner-blocks\"><\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-stackable-column stk-block-column stk-column stk-block stk-4764f29 stk-block-background\" data-v=\"4\" data-block-id=\"4764f29\"><style>.stk-4764f29 {align-self:flex-end !important;background-color:var(--theme-palette-color-8, #ffffff) !important;padding-top:0px !important;padding-right:0px !important;padding-bottom:0px !important;padding-left:0px !important;}.stk-4764f29-inner-blocks{justify-content:flex-end !important;}.stk-4764f29:before{background-color:var(--theme-palette-color-8, #ffffff) !important;}@media screen and (min-width:690px){.stk-4764f29 {flex:var(--stk-flex-grow, 1) 1 calc(40% - var(--stk-column-gap, 0px) * 2 \/ 3 ) !important;}}<\/style><div class=\"stk-column-wrapper stk-block-column__content stk-container stk-4764f29-container stk--no-background stk--no-padding\"><div class=\"stk--column-flex stk-block-content stk-inner-blocks stk-4764f29-inner-blocks\">\n<div class=\"wp-block-greenshift-blocks-container gspb_container gspb_container-gsbp-933ef16\" id=\"gspb_container-id-gsbp-933ef16\">\n<div class=\"wp-block-stackable-image stk-block-image has-text-align-left stk-block stk-1690316\" data-block-id=\"1690316\"><style>.stk-1690316 {margin-bottom:36px !important;}.stk-1690316 .stk-img-wrapper{width:50% !important;}<\/style><figure><span class=\"stk-img-wrapper stk-image--shape-stretch\"><img loading=\"lazy\" decoding=\"async\" class=\"stk-img\" src=\"https:\/\/www.ki-fortschrittszentrum.de\/wp-content\/uploads\/2025\/05\/KI-Fortschrittszentrum_308_QC_Bewerten-von-3D-Punktwolken_Logo.jpg\" width=\"50\" height=\"300\"\/><\/span><\/figure><\/div>\n\n\n\n<div class=\"wp-block-stackable-text stk-block-text stk-block stk-97d4068\" data-block-id=\"97d4068\"><style>.stk-97d4068 {margin-bottom:12px !important;}.stk-97d4068 .stk-block-text__text{font-size:16px !important;line-height:1.4em !important;font-weight:500 !important;font-style:italic !important;font-family:Constantia, Lucida Bright, Lucidabright, \"Lucida Serif\", Lucida, \"DejaVu Serif\", \"Bitstream Vera Serif\", \"Liberation Serif\", Georgia, serif !important;}@media screen and (max-width:999px){.stk-97d4068 .stk-block-text__text{font-size:16px !important;}}<\/style><p class=\"stk-block-text__text\">\"As part of the digitalization of power grids, we process hundreds of point clouds to create digital twins of high-voltage switchgear. The degree of automation of object recognition depends heavily on the quality of the point clouds. Together with the team at Fraunhofer IPA, we have successfully evaluated ML methods that we can use to carry out automated quality checks on the input data.\"<\/p><\/div>\n\n\n\n<div class=\"wp-block-greenshift-blocks-container gspb_container gspb_container-gsbp-eafe0ac\" id=\"gspb_container-id-gsbp-eafe0ac\">\n<div class=\"wp-block-stackable-text stk-block-text stk-block stk-25dc0f8\" data-block-id=\"25dc0f8\"><style>.stk-25dc0f8 {padding-top:0px !important;padding-bottom:0px !important;margin-top:0px !important;margin-bottom:0px !important;}.stk-25dc0f8 .stk-block-text__text{font-size:15px !important;}@media screen and (max-width:999px){.stk-25dc0f8 .stk-block-text__text{font-size:15px !important;}}<\/style><p class=\"stk-block-text__text has-text-align-left\">Wolfgang Eyrich<\/p><\/div>\n\n\n\n<div class=\"wp-block-stackable-text stk-block-text stk-block stk-d634667\" data-block-id=\"d634667\"><style>.stk-d634667 {align-items:flex-start !important;padding-top:0px !important;padding-bottom:0px !important;margin-top:0px !important;margin-bottom:0px !important;display:flex !important;}.stk-d634667 .stk-block-text__text{font-size:15px !important;font-weight:200 !important;}@media screen and (max-width:999px){.stk-d634667 .stk-block-text__text{font-size:15px !important;}}<\/style><p class=\"stk-block-text__text has-text-align-left\">entegra eyrich + appel gmbh<\/p><\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-greenshift-blocks-container gspb_container gspb_container-gsbp-1fa6a74\" id=\"gspb_container-id-gsbp-1fa6a74\">\n<div class=\"wp-block-stackable-text stk-block-text stk-block stk-be1fdb3\" data-block-id=\"be1fdb3\"><style>.stk-be1fdb3 {padding-top:0px !important;padding-bottom:12px !important;margin-top:0px !important;margin-bottom:0px !important;}.stk-be1fdb3 .stk-block-text__text{font-size:15px !important;color:#ffffff80 !important;}@media screen and (max-width:999px){.stk-be1fdb3 .stk-block-text__text{font-size:15px !important;}}<\/style><p class=\"stk-block-text__text has-text-color has-text-align-left\">Contact at the AI Innovation Center<\/p><\/div>\n\n\n\n<div class=\"wp-block-stackable-text stk-block-text stk-block stk-24ffa5e\" data-block-id=\"24ffa5e\"><style>.stk-24ffa5e {padding-top:0px !important;padding-bottom:0px !important;margin-top:0px !important;margin-bottom:0px !important;}.stk-24ffa5e .stk-block-text__text{font-size:15px !important;color:#ffffff !important;}@media screen and (max-width:999px){.stk-24ffa5e .stk-block-text__text{font-size:15px !important;}}<\/style><p class=\"stk-block-text__text has-text-color has-text-align-left\">Ira Effenberger<\/p><\/div>\n\n\n\n<div class=\"wp-block-stackable-button-group stk-block-button-group stk-block stk-af007b4\" data-block-id=\"af007b4\"><style>.stk-af007b4 {padding-top:0px !important;padding-right:0px !important;padding-bottom:0px !important;padding-left:0px !important;margin-top:0px !important;margin-right:0px !important;margin-bottom:0px !important;margin-left:0px !important;}<\/style><div class=\"stk-row stk-inner-blocks stk-block-content stk-button-group\">\n<div class=\"wp-block-stackable-button stk-block-button is-style-plain stk-block stk-1cf8bea\" data-block-id=\"1cf8bea\"><style>.stk-1cf8bea .stk-button{padding-top:0px !important;padding-right:0px !important;padding-bottom:0px !important;padding-left:0px !important;background:transparent !important;}.stk-1cf8bea .stk-button:hover:after{background:transparent !important;opacity:1 !important;}:where(.stk-hover-parent:hover,  .stk-hover-parent.stk--is-hovered) .stk-1cf8bea .stk-button:after{background:transparent !important;opacity:1 !important;}.stk-1cf8bea .stk-button__inner-text{font-size:15px !important;color:var(--theme-palette-color-8, #ffffff) !important;font-weight:200 !important;}@media screen and (max-width:999px){.stk-1cf8bea .stk-button__inner-text{font-size:15px !important;}}<\/style><a class=\"stk-link stk-button stk--hover-effect-darken\" href=\"mailto:ira.effenberger@ipa.fraunhofer.de\" title=\"ira.effenberger@ipa.fraunhofer.de\"><span class=\"has-text-color stk-button__inner-text\">ira.effenberger@ipa.fraunhofer.de<\/span><\/a><\/div>\n<\/div><\/div>\n<\/div>\n<\/div><\/div><\/div>\n<\/div><\/div>\n<\/div><\/div><\/div>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-stackable-spacer stk-block-spacer stk--no-padding stk-block stk-56a43b6\" data-block-id=\"56a43b6\"><\/div>\n\n\n\n<div class=\"wp-block-stackable-columns stk-block-columns stk-block stk-fc04401\" data-block-id=\"fc04401\"><style>.stk-fc04401 {padding-right:24px !important;padding-left:24px !important;}<\/style><div class=\"stk-row stk-inner-blocks stk-block-content stk-content-align stk-fc04401-column\">\n<div class=\"wp-block-stackable-column stk-block-column stk-column stk-block stk-a194320\" data-v=\"4\" data-block-id=\"a194320\"><div class=\"stk-column-wrapper stk-block-column__content stk-container stk-a194320-container stk--no-background stk--no-padding\"><div class=\"stk-block-content stk-inner-blocks stk-a194320-inner-blocks\"><div data-block=\"hook:1248\" class=\"alignfull\"><article id=\"post-1248\" class=\"post-1248\"><div class=\"entry-content is-layout-constrained\">\n<div class=\"wp-block-stackable-button-group stk-block-button-group stk-block stk-fcd1a8a\" data-block-id=\"fcd1a8a\"><style>.stk-fcd1a8a {margin-bottom:24px !important;}<\/style><div class=\"stk-row stk-inner-blocks stk-block-content stk-button-group\">\n<div class=\"wp-block-stackable-icon-button stk-block-icon-button stk-block stk-82470ba is-style-ghost\" data-block-id=\"82470ba\"><style>.stk-82470ba .stk-button{background:transparent !important;}.stk-82470ba .stk-button:hover{background:transparent !important;opacity:1 !important;}:where(.stk-hover-parent:hover,  .stk-hover-parent.stk--is-hovered) .stk-82470ba .stk-button:after{background:transparent !important;opacity:1 !important;}.stk-82470ba .stk-button:before{border-style:solid !important;border-color:var(--theme-palette-color-9, #264e5d) !important;}.stk-82470ba .stk-button .stk--inner-svg svg:last-child, .stk-82470ba .stk-button .stk--inner-svg svg:last-child :is(g, path, rect, polygon, ellipse){fill:var(--theme-palette-color-11, #006e92) !important;}<\/style><a class=\"stk-link stk-button stk--hover-effect-darken\" href=\"javascript:window.history.back();\" title=\"Back\"><span class=\"stk--svg-wrapper\"><div class=\"stk--inner-svg\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 512 512\" aria-hidden=\"true\" width=\"32\" height=\"32\"><path d=\"M9.4 233.4c-12.5 12.5-12.5 32.8 0 45.3l128 128c12.5 12.5 32.8 12.5 45.3 0s12.5-32.8 0-45.3L109.3 288 480 288c17.7 0 32-14.3 32-32s-14.3-32-32-32l-370.7 0 73.4-73.4c12.5-12.5 12.5-32.8 0-45.3s-32.8-12.5-45.3 0l-128 128z\"><\/path><\/svg><\/div><\/span><\/a><\/div>\n<\/div><\/div>\n<\/div><\/article><\/div>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block-heading--v2 stk-block stk-5cbd537\" id=\"quick-check\" data-block-id=\"5cbd537\"><style>.stk-5cbd537 {margin-bottom:0px !important;}<\/style><h1 class=\"stk-block-heading__text\">AI-supported evaluation of 3D point clouds of high-voltage switchgear<\/h1><\/div>\n\n\n\n<div class=\"wp-block-stackable-icon-label stk-block-icon-label stk-block stk-9c593c0\" id=\"quick-check\" data-block-id=\"9c593c0\"><style>.stk-9c593c0 .stk-inner-blocks{gap:8px !important;}<\/style><div class=\"stk-row stk-inner-blocks stk-block-content\">\n<div class=\"wp-block-stackable-icon stk-block-icon has-text-align-left stk-block stk-624347f\" data-block-id=\"624347f\"><style>.stk-624347f .stk--svg-wrapper .stk--inner-svg svg:last-child{height:16px !important;width:16px !important;}.stk-624347f .stk--svg-wrapper .stk--inner-svg svg:last-child, .stk-624347f .stk--svg-wrapper .stk--inner-svg svg:last-child :is(g, path, rect, polygon, ellipse){fill:var(--theme-palette-color-10, #25bae2) !important;}<\/style><span class=\"stk--svg-wrapper\"><div class=\"stk--inner-svg\"><svg style=\"height:0;width:0\"><defs><lineargradient id=\"linear-gradient-624347f\" x1=\"0\" x2=\"100%\" y1=\"0\" y2=\"0\"><stop offset=\"0%\" style=\"stop-opacity:1;stop-color:var(--linear-gradient-624347-f-color-1)\"><\/stop><stop offset=\"100%\" style=\"stop-opacity:1;stop-color:var(--linear-gradient-624347-f-color-2)\"><\/stop><\/lineargradient><\/defs><\/svg><svg data-prefix=\"fa\" data-icon=\"star\" class=\"svg-inline--fa fa-star fa-w-18\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 576 512\" aria-hidden=\"true\" width=\"32\" height=\"32\"><path fill=\"currentColor\" d=\"M259.3 17.8L194 150.2 47.9 171.5c-26.2 3.8-36.7 36.1-17.7 54.6l105.7 103-25 145.5c-4.5 26.3 23.2 46 46.4 33.7L288 439.6l130.7 68.7c23.2 12.2 50.9-7.4 46.4-33.7l-25-145.5 105.7-103c19-18.5 8.5-50.8-17.7-54.6L382 150.2 316.7 17.8c-11.7-23.6-45.6-23.9-57.4 0z\"><\/path><\/svg><\/div><\/span><\/div>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block-heading--v2 stk-block stk-cdc2d3f\" id=\"span-data-stk-dynamic-current-page-post-taxonomy-term-projektformat-contenteditable-false-class-stk-dynamic-content-quick-check-span\" data-block-id=\"cdc2d3f\"><p class=\"stk-block-heading__text\">Quick Check<\/p><\/div>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block-heading--v2 stk-block stk-c21bed1\" id=\"ausgangssituation\" data-block-id=\"c21bed1\"><h2 class=\"stk-block-heading__text\">Initial situation<\/h2><\/div>\n\n\n\n<div class=\"wp-block-stackable-text stk-block-text stk-block stk-65e3563\" data-block-id=\"65e3563\"><style>.stk-65e3563 {column-count:1 !important;}<\/style><p class=\"stk-block-text__text\">Digital twins of high-voltage switchgear are being created for the digitalization of electricity grids. The digital models are based on 3D point clouds of the systems, which are recorded using laser scanners. However, the degree of automation in the creation of the digital twin depends largely on the quality of the point cloud. The weather conditions, the devices and software products used, as well as the procedure during scanning can influence the quality of the resulting 3D point cloud. For efficient digitization of high-voltage switchgear, the quality of the point clouds is therefore checked first. This previously manual inspection and evaluation of the point cloud quality is very time-consuming and also not objective. This process is therefore to be automated and an AI-based assessment of the point cloud quality is to be investigated as part of the quick check.<\/p><\/div>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block-heading--v2 stk-block stk-8c26049\" id=\"losungsidee\" data-block-id=\"8c26049\"><h2 class=\"stk-block-heading__text\">Solution idea<\/h2><\/div>\n\n\n\n<div class=\"wp-block-stackable-text stk-block-text stk-block stk-ab6a506\" data-block-id=\"ab6a506\"><style>.stk-ab6a506 {column-count:1 !important;}<\/style><p class=\"stk-block-text__text\">In the scans of the high-voltage switchgear, statements about the quality of the scan data are to be generated automatically. The evaluation is to be carried out on the basis of the lines. This approach has several advantages. Lines have a high availability in the data. Furthermore, the geometry of the cables is known, as they can be modeled approximately as cylinders. Therefore, the pipes in the 3D point clouds are first segmented using AI. The quality of the point clouds is evaluated by analyzing the segmented pipes. The point cloud of the system is analyzed with AI at several hundred points so that a clear statistical statement about the quality of the point cloud can be made.<\/p><\/div>\n\n\n\n<div class=\"wp-block-stackable-image stk-block-image has-text-align-left stk-block stk-2fa484b\" data-block-id=\"2fa484b\"><style>.stk-2fa484b .stk-img-figcaption{font-size:12px !important;}.stk-2fa484b .stk-img-wrapper{width:856px !important;}@media screen and (max-width:999px){.stk-2fa484b .stk-img-figcaption{font-size:12px !important;}}<\/style><figure><span class=\"stk-img-wrapper stk-image--shape-stretch stk--has-lightbox\"><img loading=\"lazy\" decoding=\"async\" class=\"stk-img wp-image-2795\" src=\"https:\/\/www.ki-fortschrittszentrum.de\/wp-content\/uploads\/2025\/05\/KI-Fortschrittszentrum_308_QC_Bewerten-von-3D-Punktwolken_Abb1.png\" width=\"856\" height=\"247\" alt=\"Figure 1: Color-coded evaluation of the quality of the point cloud, Fraunhofer IPA\" srcset=\"https:\/\/www.ki-fortschrittszentrum.de\/wp-content\/uploads\/2025\/05\/KI-Fortschrittszentrum_308_QC_Bewerten-von-3D-Punktwolken_Abb1.png 856w, https:\/\/www.ki-fortschrittszentrum.de\/wp-content\/uploads\/2025\/05\/KI-Fortschrittszentrum_308_QC_Bewerten-von-3D-Punktwolken_Abb1-400x115.png 400w, https:\/\/www.ki-fortschrittszentrum.de\/wp-content\/uploads\/2025\/05\/KI-Fortschrittszentrum_308_QC_Bewerten-von-3D-Punktwolken_Abb1-698x201.png 698w, https:\/\/www.ki-fortschrittszentrum.de\/wp-content\/uploads\/2025\/05\/KI-Fortschrittszentrum_308_QC_Bewerten-von-3D-Punktwolken_Abb1-768x222.png 768w, https:\/\/www.ki-fortschrittszentrum.de\/wp-content\/uploads\/2025\/05\/KI-Fortschrittszentrum_308_QC_Bewerten-von-3D-Punktwolken_Abb1-18x5.png 18w\" sizes=\"auto, (max-width: 856px) 100vw, 856px\" \/><\/span><figcaption class=\"stk-img-figcaption\">Figure 1: Color-coded evaluation of the quality of the point cloud, Fraunhofer IPA<\/figcaption><\/figure><\/div>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block-heading--v2 stk-block stk-76475ee\" id=\"nutzen\" data-block-id=\"76475ee\"><h2 class=\"stk-block-heading__text\">Benefit<\/h2><\/div>\n\n\n\n<div class=\"wp-block-stackable-text stk-block-text stk-block stk-3e86ca0\" data-block-id=\"3e86ca0\"><p class=\"stk-block-text__text\">Models of the existing switchgear are necessary for the digitalization of the electricity grid. Due to the large number of switchgears, a high degree of automation is required for digitization. In this Quick Check, the first step of the processing pipeline - evaluating the scan quality - was considered. By automatically evaluating the quality of the point cloud, the manual, monotonous and time-consuming inspection of the scans can be replaced. Since the AI-based assessment of scan quality is carried out on hundreds of locations in the point cloud, it is not a random check, but provides a complete and detailed picture. In addition, the assessment is reproducible and does not depend on experience or the subjective assessment of a manual inspection.<\/p><\/div>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block-heading--v2 stk-block stk-1e747a7\" id=\"umsetzung-der-ki-applikation\" data-block-id=\"1e747a7\"><h2 class=\"stk-block-heading__text\">Implementation of the AI application<\/h2><\/div>\n\n\n\n<div class=\"wp-block-stackable-text stk-block-text stk-block stk-d745445\" data-block-id=\"d745445\"><p class=\"stk-block-text__text\">Already digitized switchgear serves as the basis for training the AI algorithm. Training data is automatically generated from these systems by feeding the information from the already generated digital twins back into the initial clouds. The developed network derives local geometric features from the point cloud. These local features are combined with each other until features with high semantic meaning are created, on the basis of which the lines can be segmented from the point cloud. For a point-by-point segmentation of the 3D point cloud, the global features are combined with the local features.<\/p><\/div>\n<\/div><\/div><\/div>\n<\/div><\/div>\n\n\n\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>The quality of the scanned point clouds is crucial for the creation of digital twins for high-voltage switchgear. By using AI methods, the point clouds can be evaluated automatically.<\/p>","protected":false},"author":4,"featured_media":2796,"template":"","format":"standard","meta":{"_acf_changed":true,"_gspb_post_css":".gspb_container-id-gsbp-1fa6a74,.gspb_container-id-gsbp-933ef16,.gspb_container-id-gsbp-eafe0ac{flex-direction:column;box-sizing:border-box}#gspb_container-id-gsbp-1fa6a74.gspb_container>p:last-of-type,#gspb_container-id-gsbp-933ef16.gspb_container>p:last-of-type,#gspb_container-id-gsbp-eafe0ac.gspb_container>p:last-of-type{margin-bottom:0}#gspb_container-id-gsbp-933ef16.gspb_container{position:relative;padding:24px}#gspb_container-id-gsbp-eafe0ac.gspb_container{position:relative;display:block;margin-left:auto}#gspb_container-id-gsbp-1fa6a74.gspb_container{position:relative;display:block;margin:0;padding:24px;background-color:var(--wp--preset--color--palette-color-11, var(--theme-palette-color-11, #006e92))}"},"bereich":[20,24],"institut":[],"projektformat":[14],"class_list":["post-573","projekt","type-projekt","status-publish","format-standard","has-post-thumbnail","hentry","bereich-entwicklung-innovation","bereich-produktion-qualitaetsmanagement","projektformat-quick-check"],"blocksy_meta":[],"acf":[],"_links":{"self":[{"href":"https:\/\/www.ki-fortschrittszentrum.de\/en\/wp-json\/wp\/v2\/projekt\/573","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ki-fortschrittszentrum.de\/en\/wp-json\/wp\/v2\/projekt"}],"about":[{"href":"https:\/\/www.ki-fortschrittszentrum.de\/en\/wp-json\/wp\/v2\/types\/projekt"}],"author":[{"embeddable":true,"href":"https:\/\/www.ki-fortschrittszentrum.de\/en\/wp-json\/wp\/v2\/users\/4"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.ki-fortschrittszentrum.de\/en\/wp-json\/wp\/v2\/media\/2796"}],"wp:attachment":[{"href":"https:\/\/www.ki-fortschrittszentrum.de\/en\/wp-json\/wp\/v2\/media?parent=573"}],"wp:term":[{"taxonomy":"bereich","embeddable":true,"href":"https:\/\/www.ki-fortschrittszentrum.de\/en\/wp-json\/wp\/v2\/bereich?post=573"},{"taxonomy":"institut","embeddable":true,"href":"https:\/\/www.ki-fortschrittszentrum.de\/en\/wp-json\/wp\/v2\/institut?post=573"},{"taxonomy":"projektformat","embeddable":true,"href":"https:\/\/www.ki-fortschrittszentrum.de\/en\/wp-json\/wp\/v2\/projektformat?post=573"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}