A Lightweight Open-Source Framework for Packaging Visualization and Data Automation

This paper presents a low-complexity, open-source platform designed to empower small and medium-sized enterprises (SMEs) in the premium business to business (B2B) packaging industry with advanced digital capabilities for product personalization and rapid design visualization. Addressing the sector’s persistent barriers such as limited IT resources, manual workflows, and lack of structured supplier data access, the proposed system integrates dynamic web scraping for automated supplier data acquisition with real-time image processing for printable area detection on packaging components, particularly bottles. Leveraging open-source tools like Beautiful Soup, OpenCV, and Shapely, the platform eliminates reliance on time-intensive manual integration and supports agile, data-driven design workflows. The development process is guided by human-centered design principles to ensure usability and alignment with SME operational realities. Results demonstrate that this approach significantly streamlines catalog management and design preparation, offering a scalable pathway for SMEs to achieve digital transformation and maintain competitive differentiation in an increasingly digitalized packaging market.

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Publication Details

Journal
Procedia Computer Science
Published
2026-01-01
DOI
https://doi.org/10.1016/j.procs.2026.02.227
Primary Topic
Consumer Packaging Perceptions and Trends
Type
article
Field-Weighted Citation Impact
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article

A Lightweight Open-Source Framework for Packaging Visualization and Data Automation

Shantall Cisneros Saldana, Sampat Acharya, Heike Markus
Procedia Computer Science
Consumer Packaging Perceptions and Trends
article

A Lightweight Open-Source Framework for Packaging Visualization and Data Automation

Shantall Cisneros Saldana, Sampat Acharya, Heike Markus
article en

Abstract

This paper presents a low-complexity, open-source platform designed to empower small and medium-sized enterprises (SMEs) in the premium business to business (B2B) packaging industry with advanced digital capabilities for product personalization and rapid design visualization. Addressing the sector’s persistent barriers such as limited IT resources, manual workflows, and lack of structured supplier data access, the proposed system integrates dynamic web scraping for automated supplier data acquisition with real-time image processing for printable area detection on packaging components, particularly bottles. Leveraging open-source tools like Beautiful Soup, OpenCV, and Shapely, the platform eliminates reliance on time-intensive manual integration and supports agile, data-driven design workflows. The development process is guided by human-centered design principles to ensure usability and alignment with SME operational realities. Results demonstrate that this approach significantly streamlines catalog management and design preparation, offering a scalable pathway for SMEs to achieve digital transformation and maintain competitive differentiation in an increasingly digitalized packaging market.

Procedia Computer ScienceVol. 277
Hof University of Applied Sciences (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 9%
Consumer Packaging Perceptions and Trends
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A Lightweight Open-Source Framework for Packaging Visualization and Data Automation — Shantall Cisneros Saldana, Sampat Acharya, et al. · Procedia Computer Science (2026) | TGRS Research Map | TGRS