Digitizing Scrum Boards via Computer Vision
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Solution Overview
Problem
The Scrum methodology relies on physical paper notes for task management, which requires manual processing and summation of point values, lacking efficient digitalization and automation for project planning.
Innovation Solution
A system utilizing computer vision algorithms and a digital camera to digitize handwritten notes, convert them into character strings, and group by color for generating charts and summary statistics, combining the benefits of physical notes with automated tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If physical paper notes are used for task management, then flexibility and ease of manipulation are improved, but manual processing and summation of point values become time-consuming and labor-intensive
Solution Approach 1:
The system creates a digital copy of the physical Scrum board by capturing an image with a camera and processing it through computer vision algorithms. This digital replica maintains the visual layout and information of the physical notes while enabling automated analysis, thereby preserving the tactile benefits of physical notes while eliminating manual processing time.
Solution Approach 2:
The patent replaces manual mechanical operations (physically moving notes, manually summing points) with automated computer vision and image processing systems. The system automatically detects note positions, extracts text, identifies colors, and calculates point totals, substituting human manual labor with automated computational processes.
2Ease of operation
If physical notes are used for project planning, then visual organization and group discussion are enhanced, but automated tracking and digital processing are lacking
Solution Approach 1:
The system creates a digital copy of the physical Scrum board that preserves all visual organizational elements (layout, colors, groupings) while adding automated tracking capabilities. The computer vision system processes the captured image to extract structured data, enabling both visual organization and automated analysis simultaneously.
Solution Approach 2:
The system makes the physical note system multi-functional by combining the visual organization benefits of physical notes with the automated tracking capabilities of digital systems. The same physical notes serve both as visual aids for discussion and as data sources for automated point calculation and progress tracking.
3Loss of information
If dozens of separate physical notes with varying point values are used, then detailed task tracking is achieved, but repeated manual summing is required to determine target achievement
Solution Approach 1:
The system replaces manual counting and summing operations with automated computer vision and image processing. The system automatically detects each note's point value through text recognition, extracts the information digitally, and performs calculations without human intervention, dramatically improving productivity while maintaining detailed tracking accuracy.
Solution Approach 2:
The system creates a digital representation of all note information including point values, enabling automated processing of the data. This digital copy allows for instant calculation and analysis of point totals across all notes without requiring manual enumeration.
Data Source
AI summary
A method of managing notes for project planning such as the Scrum methodology. The method obtains a digital image of a board having physical notes with task information and point values. The notes in the digital image are separated, and handwriting in the notes is converted to corresponding character strings for the task information and point values. A color is detected for each of the notes in order to create color-coded groups of the notes. The method outputs the color-coded groups with the corresponding character strings, which can be used to generate charts relating to the Scrum board.