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Zühlke",{"tag":10,"attributes":190},{"name":191,"content":192},"twitter:site:id","247189965",{"tag":10,"attributes":194},{"name":195,"content":90},"twitter:image:alt",{"tag":10,"attributes":197},{"name":198,"content":199},"twitter:image","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Fmax_1300x1300\u002Fpublic\u002Fimages\u002Fecm-photo-2.jpg?itok=4aY2j-Ep,https:\u002F\u002Fwww.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fimages\u002Fzuhlke_innovation_social.jpg",{"tag":10,"attributes":201},{"name":202,"content":203},"google-site-verification","VEzolc1Vxy1KyRIlIqUSmVS7fqP_3_ZeBqPRby4g2mE",{"tag":205},"script","6547","\u002Fde\u002Fcase-studies\u002Fder-earth-control-measure-evaluator-des-pub-entwicklung-eines-prototyps-mit","Der Earth Control Measure Evaluator des PUB: Entwicklung eines Prototyps mit maschinellem Lernen ",[210,214],{"path":211,"langcode":212},"\u002Fen\u002Fcase-studies\u002Fpubs-earth-control-measure-evaluator-building-a-prototype-powered-by-machine-learning",{"id":213},"en",{"path":207,"langcode":215},{"id":216},"de",{"id":218,"sharedMediaLegend":219,"mediaImage":220,"name":240},"6294",null,{"url":221,"width":222,"height":223,"alt":224,"title":219,"size":225,"mime":226,"variations":219,"headerMinimalVariations":227},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fimages\u002Fecm-photo-2.jpg",626,418,"PUB Earth Control Measure",65816,"image\u002Fjpeg",[228,231,232,236,239],{"name":229,"url":230,"width":222,"height":223},"FOCAL_POINT32_SMALL","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_3_2_small\u002Fpublic\u002Fimages\u002Fecm-photo-2.jpg.webp?itok=nOau67OE",{"name":229,"url":230,"width":222,"height":223},{"name":233,"url":234,"width":222,"height":235},"FOCAL_POINT169_MEDIUM","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_16_9_medium\u002Fpublic\u002Fimages\u002Fecm-photo-2.jpg.webp?itok=4DS9HMZ-",353,{"name":237,"url":238,"width":222,"height":235},"FOCAL_POINT169_LARGE","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_16_9_large\u002Fpublic\u002Fimages\u002Fecm-photo-2.jpg.webp?itok=akgnSZS2",{"name":237,"url":238,"width":222,"height":235},"ecm-photo-2.jpg","Prototyping des Earth Control Measure Evaluator von PUB, der auf maschinellem Lernen basiert",{"processed":243},"\u003Cp>Erfahren Sie, wie wir PUB, Singapurs Nationale Wasserbehörde, dabei geholfen haben, einen End-to-End-Prototyp in der Cloud zu erstellen und dabei maschinelle Lerntechnologie zu nutzen, um den Zeitaufwand für manuelle Überprüfungen zu reduzieren und gleichzeitig Fehler genau zu identifizieren.\u003C\u002Fp>",{"id":218,"sharedMediaLegend":219,"mediaImage":245,"name":240},{"url":221,"width":222,"height":223,"alt":224,"title":219,"size":225,"mime":226,"variations":219},{"id":247,"sharedMediaLegend":219,"mediaImage":248,"name":255},"5690",{"url":249,"width":250,"height":251,"alt":252,"title":219,"size":253,"mime":254,"variations":219},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fimages\u002Fpub.png",900,500,"Singapore Public Utilities Board",8415,"image\u002Fpng","pub.png",[257,264,269,295,301],{"__typename":258,"id":259,"ctaLink":219,"pgSharedText":260,"pgSharedTitle":219,"pgSharedCtaLink":219},"ParagraphPgText","23776",{"value":261,"processed":262,"format":263},"\u003Cul>\r\n\t\u003Cli>\r\n\t\u003Cp class=\"text-lead\">Bei der Wasserbehörde von Singapur gehen jedes Jahr über 1500 Zeichnungen ein, deren manuelle Prüfung Zeit und ein geübtes Auge braucht.\u003C\u002Fp>\r\n\t\u003C\u002Fli>\r\n\t\u003Cli>\r\n\t\u003Cp class=\"text-lead\">Die Herausforderung? Wie lässt sich mit maschinellem Lernen der Zeitaufwand bei der manuellen Prüfung reduzieren, ohne Fehler zu übersehen?\u003C\u002Fp>\r\n\t\u003C\u002Fli>\r\n\t\u003Cli>\r\n\t\u003Cp class=\"text-lead\">Hier erfahren Sie, wie in der Cloud ein vollständiger Prototyp entwickelt und für die Erkennung bestehender Zeichnungen und darin vorkommender häufiger Fehler trainiert wurde, um den Gesamtprozess zu optimieren.\u003C\u002Fp>\r\n\t\u003C\u002Fli>\r\n\u003C\u002Ful>\r\n","\u003Cul>\n\t\u003Cli>\n\t\u003Cp class=\"text-lead\">Bei der Wasserbehörde von Singapur gehen jedes Jahr über 1500 Zeichnungen ein, deren manuelle Prüfung Zeit und ein geübtes Auge braucht.\u003C\u002Fp>\n\t\u003C\u002Fli>\n\t\u003Cli>\n\t\u003Cp class=\"text-lead\">Die Herausforderung? Wie lässt sich mit maschinellem Lernen der Zeitaufwand bei der manuellen Prüfung reduzieren, ohne Fehler zu übersehen?\u003C\u002Fp>\n\t\u003C\u002Fli>\n\t\u003Cli>\n\t\u003Cp class=\"text-lead\">Hier erfahren Sie, wie in der Cloud ein vollständiger Prototyp entwickelt und für die Erkennung bestehender Zeichnungen und darin vorkommender häufiger Fehler trainiert wurde, um den Gesamtprozess zu optimieren.\u003C\u002Fp>\n\t\u003C\u002Fli>\n\u003C\u002Ful>","full_html",{"__typename":258,"id":265,"ctaLink":219,"pgSharedText":266,"pgSharedTitle":219,"pgSharedCtaLink":219},"14703",{"value":267,"processed":268,"format":263},"\u003Cp>Situated near the equator, Singapore has a typically tropical climate with abundant rainfall. It rains an average of 167 days a year, with an annual total rainfall of around 2,500mm. During heavy rainfall, silt can be washed from exposed earth surfaces in construction sites into waterways. Good Earth Control Measures (ECM) implemented in construction sites prevent silty runoff from being washed into waterways, keeping them clean and beautiful.\u003C\u002Fp>\r\n\r\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.pub.gov.sg\u002F\">PUB, Singapore’s national water agency\u003C\u002Fa>, receives more than 1,500 drawing submissions per year seeking approval for construction works that require Earth Control Measures (ECM) to be implemented. This process requires time as well as an experienced eye to manually review the drawings and ensure that the ECMs are properly designed.\u003C\u002Fp>\r\n","\u003Cp>Situated near the equator, Singapore has a typically tropical climate with abundant rainfall. It rains an average of 167 days a year, with an annual total rainfall of around 2,500mm. During heavy rainfall, silt can be washed from exposed earth surfaces in construction sites into waterways. Good Earth Control Measures (ECM) implemented in construction sites prevent silty runoff from being washed into waterways, keeping them clean and beautiful.\u003C\u002Fp>\n\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.pub.gov.sg\u002F\">PUB, Singapore’s national water agency\u003C\u002Fa>, receives more than 1,500 drawing submissions per year seeking approval for construction works that require Earth Control Measures (ECM) to be implemented. This process requires time as well as an experienced eye to manually review the drawings and ensure that the ECMs are properly designed.\u003C\u002Fp>",{"__typename":270,"id":271,"caption":219,"imageRight":219,"pgSharedTitle":272,"pgSharedCtaLink":219,"textMedia":273,"pgSharedText":292},"ParagraphPgTextMedia","14704","Improve process efficiency with machine learning",{"id":274,"sharedMediaLegend":219,"mediaImage":275,"name":291},"5692",{"url":276,"width":277,"height":278,"alt":279,"title":219,"size":280,"mime":254,"variations":219,"textMediaVariations":281},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fimages\u002Fpub-automated-earth-control-measure-submission-evaluator.png",869,610,"PUB - Automated Earth Control Measure Submission Evaluator",101948,[282,285,286,287,290],{"name":283,"url":284,"width":277,"height":278},"FIXED_WIDTH_SMALL","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffixed_width_small\u002Fpublic\u002Fimages\u002Fpub-automated-earth-control-measure-submission-evaluator.png.webp?itok=JXUlJK1P",{"name":283,"url":284,"width":277,"height":278},{"name":283,"url":284,"width":277,"height":278},{"name":288,"url":289,"width":277,"height":278},"FIXED_WIDTH_MEDIUM","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffixed_width_medium\u002Fpublic\u002Fimages\u002Fpub-automated-earth-control-measure-submission-evaluator.png.webp?itok=UlBkzyAX",{"name":288,"url":289,"width":277,"height":278},"pub-automated-earth-control-measure-submission-evaluator.png",{"value":293,"processed":294,"format":263},"\u003Cp>Together with PUB, Zühlke found a way to augment the existing workflow using machine learning. Machine learning algorithms can analyze the input plans drawing and verify their design against ECM rules for compliance. Such an augmentation could reduce the overall time necessary to spend on verifying these plans by handling the more standardized cases and only requesting feedback from PUB officers for cases with higher complexity.\u003C\u002Fp>\r\n","\u003Cp>Together with PUB, Zühlke found a way to augment the existing workflow using machine learning. Machine learning algorithms can analyze the input plans drawing and verify their design against ECM rules for compliance. Such an augmentation could reduce the overall time necessary to spend on verifying these plans by handling the more standardized cases and only requesting feedback from PUB officers for cases with higher complexity.\u003C\u002Fp>",{"__typename":258,"id":296,"ctaLink":219,"pgSharedText":297,"pgSharedTitle":300,"pgSharedCtaLink":219},"14706",{"value":298,"processed":299,"format":263},"\u003Cp>Over a span of four months, the team built a corresponding end-to-end prototype incorporating:\u003C\u002Fp>\r\n\r\n\u003Cul>\r\n\t\u003Cli>Multiple models of computer vision (object detection and instance segmentation) trained on past ECM submissions to recognise key design elements\u003C\u002Fli>\r\n\t\u003Cli>Optical character recognition to extract relevant text\u003C\u002Fli>\r\n\t\u003Cli>Rule engine to check compliance based on the recognitions and a prototypical user interface to interact with PUB officers.\u003C\u002Fli>\r\n\u003C\u002Ful>\r\n","\u003Cp>Over a span of four months, the team built a corresponding end-to-end prototype incorporating:\u003C\u002Fp>\n\n\u003Cul>\n\t\u003Cli>Multiple models of computer vision (object detection and instance segmentation) trained on past ECM submissions to recognise key design elements\u003C\u002Fli>\n\t\u003Cli>Optical character recognition to extract relevant text\u003C\u002Fli>\n\t\u003Cli>Rule engine to check compliance based on the recognitions and a prototypical user interface to interact with PUB officers.\u003C\u002Fli>\n\u003C\u002Ful>","Scale implementation with speed and accuracy",{"__typename":258,"id":302,"ctaLink":219,"pgSharedText":303,"pgSharedTitle":306,"pgSharedCtaLink":219},"14705",{"value":304,"processed":305,"format":263},"\u003Cp>Thorough analysis of the algorithms’ performance has identified the working scenarios and their shortcomings. The prototype is deployed on Amazon Web Services (AWS), allowing to further probe the models with new data. In combination, these findings allow to adjust the business case and steer the submission format towards desired standardisation levels.\u003C\u002Fp>\r\n\r\n\u003Cp> \u003C\u002Fp>\r\n\r\n\u003Cp>More about the \u003Ca href=\"https:\u002F\u002Fwww.pub.gov.sg\u002Finnovationchallenge\u002Fchallenges\u002Fpast\u002Fautomated-earth-control-measure-submission-evaluator\">Automated Earth Control Measure Submission Evaluator innovation challenge\u003C\u002Fa>.\u003C\u002Fp>\r\n","\u003Cp>Thorough analysis of the algorithms’ performance has identified the working scenarios and their shortcomings. The prototype is deployed on Amazon Web Services (AWS), allowing to further probe the models with new data. In combination, these findings allow to adjust the business case and steer the submission format towards desired standardisation levels.\u003C\u002Fp>\n\n\n\n\u003Cp>More about the \u003Ca href=\"https:\u002F\u002Fwww.pub.gov.sg\u002Finnovationchallenge\u002Fchallenges\u002Fpast\u002Fautomated-earth-control-measure-submission-evaluator\">Automated Earth Control Measure Submission Evaluator innovation challenge\u003C\u002Fa>.\u003C\u002Fp>","Designed for sustainable growth",[308],{"id":309,"name":310},"120","Öffentlicher Sektor & 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