{"id":7691,"date":"2026-09-11T11:52:51","date_gmt":"2026-09-11T09:52:51","guid":{"rendered":"https:\/\/www.scs.ch\/uncategorized-en-us\/digitization-of-cable-diagrams\/"},"modified":"2026-09-20T07:38:59","modified_gmt":"2026-09-20T05:38:59","slug":"digitization-of-cable-diagrams","status":"publish","type":"post","link":"https:\/\/www.scs.ch\/en\/case-studies\/digitization-of-cable-diagrams\/","title":{"rendered":"Digitization of Cable Diagrams"},"content":{"rendered":"

Initial Situation<\/h2><\/div>

Banedanmark needs to digitize more than 10,000 cable diagrams. This information must be available quickly, particularly during construction work, so that existing lines can be reliably taken into account and damage avoided. The cable diagrams vary greatly in age, quality, and scale, and their information density is enormous. Purely manual digitization would take several years. <\/p>\n<\/div>

\"Schwarz-wei\u00dfe<\/span><\/div><\/div><\/div>

Project Overview<\/h3><\/div>

Client<\/strong>
Banedanmark (Danish State Railways)<\/p>\n<\/div>

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Sector<\/strong>
Public Transport<\/p>\n<\/div>

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Solution<\/strong>
Automated digitization of thousands of cable diagrams.<\/p>\n<\/div>

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System Environment <\/strong>
Over 10,000 cable diagrams of varying age, quality, and scale<\/p>\n<\/div>

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Approach <\/strong>
Gradually increasing automation through human-machine collaboration<\/p>\n<\/div>

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Award<\/strong>
Ranked in Banedanmark’s international competition for ideas<\/p>\n<\/div><\/div><\/div><\/div><\/div>

The SCS Contribution<\/h2><\/div>

SCS developed an automation concept designed to gradually reduce manual work steps. Human corrections provide new training data, enabling learning systems to take over an increasing number of tasks. <\/p>\n<\/div><\/div><\/div>

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Learning with Every Correction<\/h4><\/div>
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Human and machine work closely together in this concept. Manually verified and corrected results improve the database, allowing further work steps to be automated gradually. <\/p>\n<\/div><\/div><\/div>

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Ground Truth Built Efficiently<\/h4><\/div>
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Learning systems require reliably labeled training data. The SCS concept reduces the effort required by systematically combining existing diagrams with already known information. <\/p>\n<\/div><\/div><\/div>

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Historical Diagrams Combined<\/h4><\/div>
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Diagrams from different decades often exist for the same location. The concept localizes and overlays these documents. Known information in one diagram can thus help assign previously unknown details in another, similar to the principle of the Rosetta Stone. <\/p>\n<\/div><\/div><\/div>

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Diagrams Localized Step by Step<\/h4><\/div>
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First, character recognition is used to roughly determine which station or track section a diagram belongs to. The concept then provides for fine localization, for example by matching street structures with map data. Based on this, relevant objects can be recognized and additional object types can be trained. <\/p>\n<\/div><\/div><\/div>

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Result<\/h2><\/div>

The SCS concept won Banedanmark’s international competition for ideas and expanded the technological solution space for the digitization of more than 10,000 cable diagrams. According to SCS, the developed approaches are being integrated into the actual project implementation. Instead of recording every historical diagram completely by hand, the concept combines multiple information sources and human corrections with learning processes. This should allow more and more steps of the digitization process to be automated. <\/p>\n<\/div><\/div><\/div>

Over 10,000 diagrams<\/h3><\/div>

to be digitally accessible at Banedanmark.<\/p>\n<\/div><\/div><\/div>

1st Place<\/h3><\/div>

in the international competition for ideas.<\/p>\n<\/div><\/div><\/div>

Human Plus Machine<\/h3><\/div>

Corrections gradually improve the database.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

Services Utilized<\/h2><\/div><\/div><\/div>

Algorithms, ML & AI<\/h3><\/div><\/div><\/div><\/div><\/div><\/div>

Computer Vision<\/h3><\/div><\/div><\/div><\/div><\/div><\/div>

Public Transport<\/h3><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>
\"The<\/div><\/div>

Your Contact Person<\/h2><\/div>
Pascal Iselin<\/div><\/div>

Algorithms, Analytics & AI
+41 43 456 16 00<\/a><\/p>\n<\/div>

Speak with the responsible specialist<\/span>Speak with the responsible specialist<\/span><\/div><\/a><\/div>

For questions regarding machine learning, document analysis, and the automation of data-intensive digitization tasks.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

Further Case Studies<\/h2><\/div>