Sew Guider: A Smart Sewing Guide Machine for Assisting Garment Creation
DOI:
https://doi.org/10.5281/zenodo.19874735Keywords:
Sewing Education, Machine Vision, Real-Time Error Detection, Raspberry Pi System, Interactive Learning ToolAbstract
This study addresses the need for an interactive, technology-driven learning tool to enhance sewing education among young individuals and students. Utilizing a Developmental Research methodology and a Modified Prototype Model, the system integrates machine vision, a webcam, and a touchscreen interface to provide near real-time sewing guidance and error detection. The system delivers step-by-step instructions in a game-like environment across five progressive learning levels, monitoring stitch accuracy and alerting users to errors. The system was implemented on a Raspberry Pi 4 Model B 8GB and developed using Python, OpenCV for HSV color detection, Pygame for graphical user interface and pattern overlay rendering, and YOLOv8n-seg and YOLOv8n for near real-time needle detection. A fixed green pattern overlay is displayed on the Raspberry Pi Monitor for users to follow, and stitches are classified as cyan for correct and red for incorrect, with accuracy computed using the formula Score = detected stitch coverage divided by the overlay pattern multiplied 100%. A portable sewing machine and a Juki embroidery machine serve as the primary and secondary hardware components for the learning sessions. In the testing and evaluation phase, ISO 25010:2011 standard surveys were used to assess the system's functionality, reliability, usability, and maintainability. The study concludes that Sew Guider demonstrated its effectiveness as a guided learning tool for practicing basic sewing skills.
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Copyright (c) 2026 Tyron Nicoli Maclang, Eugene Espolo, Jimuel San Juan, Ron Cristian Mendoza, Lech Walesa Navarra
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