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Printing E-Commerce Platform Using 3Dimensional with AI Voice Assistance
Subject area: Science,Engineering and Technology · Area of research: Graphics & Design
DOI: https://doi.org/10.64388/IREV10I1-1719484
Abstract
The proliferation of additive manufacturing technology has created demand for accessible online platforms enabling end-users to order customized 3D printed products. However, existing solutions lack integrated workflows combining user-uploaded image processing, automated 3D reconstruction, interactive visualization, and secure transaction capabilities. This research presents a novel web-based e-commerce platform that employs photogrammetry algorithms to transform multi-angle user photographs into printable 3D models while providing comprehensive e-commerce functionalities including product cataloging, real-time 3D visualization, secure payment integration, and administrative order management. The system architecture integrates React.js frontend framework with Tailwind CSS styling, Three.js-based 3D rendering engines, photogrammetry reconstruction pipelines, and secure payment gateway APIs. Implementation results demonstrate successful reconstruction of 3D models from image sets with appropriate feature detection accuracy, mesh optimization for manufacturability, and seamless user experience across the complete workflow from image upload through product delivery. Performance evaluation indicates average construction time of 2-5 minutes for 30-60 image datasets and successful generation of STL files compatible with standard FDM printing workflows. The platform addresses market gaps in accessible custom 3D printing services while maintaining production quality standards and user-friendly interfaces suitable for non-technical audiences including hobbyists, students, and small enterprises.
Keywords
3D Printing, Additive Manufacturing, E-Commerce Platform, Photogrammetry, React Web Application, STL File Generation
How to cite this paper
@article{1719484,
author = {Sumana M},
title = {Printing E-Commerce Platform Using 3Dimensional with AI Voice Assistance},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {1},
pages = {411-422},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1719484.pdf},
abstract = {The proliferation of additive manufacturing technology has created demand for accessible online platforms enabling end-users to order customized 3D printed products. However, existing solutions lack integrated workflows combining user-uploaded image processing, automated 3D reconstruction, interactive visualization, and secure transaction capabilities. This research presents a novel web-based e-commerce platform that employs photogrammetry algorithms to transform multi-angle user photographs into printable 3D models while providing comprehensive e-commerce functionalities including product cataloging, real-time 3D visualization, secure payment integration, and administrative order management. The system architecture integrates React.js frontend framework with Tailwind CSS styling, Three.js-based 3D rendering engines, photogrammetry reconstruction pipelines, and secure payment gateway APIs. Implementation results demonstrate successful reconstruction of 3D models from image sets with appropriate feature detection accuracy, mesh optimization for manufacturability, and seamless user experience across the complete workflow from image upload through product delivery. Performance evaluation indicates average construction time of 2-5 minutes for 30-60 image datasets and successful generation of STL files compatible with standard FDM printing workflows. The platform addresses market gaps in accessible custom 3D printing services while maintaining production quality standards and user-friendly interfaces suitable for non-technical audiences including hobbyists, students, and small enterprises.},
keywords = {3D Printing, Additive Manufacturing, E-Commerce Platform, Photogrammetry, React Web Application, STL File Generation},
month = {July},
doi = {https://doi.org/10.64388/IREV10I1-1719484}
}