Leading IT Company envisioned to automate data processing from blueprints for Electrical Engineers
The client is a global professional services firm focused on delivering digital transformation for their clients, putting digital and data to work to create competitive advantage.
The client is a global professional services firm focused on delivering digital transformation for their clients, putting digital and data to work to create a competitive advantage.
The client wanted to create a solution for electrical engineers, enabling them to derive meaningful data from electrical blueprints to enable informed decision-making on costs.
The team, after understanding the client’s process, architected a solution that would use Computer Vision and Machine learning to extract data. This data was further processed to provide actionable information.
Convert blueprints into images for further processing in computer vision
Provide data processing based on predefined rules
Ensure deep learning to make the tool more intelligent with time
The client was able to provide a solution that processed blueprints to provide actionable information. They were able to capture the market that was struggling to make use of their data.
The client through its innovative solution wanted to equip electrical engineers with meta-information on their blue-prints at the click of a button. Existing solutions were limited to giving data using OCR tools. Such solutions gave
Limited Use: Error-prone data – output data was dependent on the quality of input data; and was therefore not reliable
In-efficient process – OCR tools only provided Image capture and not data capture. Data still had to be typed in using manual, error-prone methods
By itself, typed-in data with image capture couldn’t provide any actionable information to the engineers.
The team determined the steps required in providing actionable information from blueprints. Trantor chose Python as the software language. Keeping the blueprint in mind, they chose Computer vision and Machine learning in the backend to convert blueprints into Images and images to data. This data was further processed into structure format by using predefined rule sets.
Blueprints were converted into Images for Computer vision and Machine Learning(ML).
The processing flow was tailored to the characteristics of the source material
Using Computer Vision, the regions where detected in which the relevant data was present.
Machine learning was used for data extraction from detected regions.
Data was processed using built-in business rule sets
Processed data was moved into the server for easy retrieval and search;
Intuitive, user-friendly UI was designed and built to allow end users to convert blueprints into actionable data in a few clicks
30% improvement in bottom-line due to informed decision-making
60% reduction in operational cost
95% of data accuracy
=Technologies:
Python
ROR
Open CV
Machine Learning (KERAS)
Tesseract APIs
Industry: IT Services