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

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Τίτλος: A Lightweight Open-Source Framework for Packaging Visualization and Data Automation.
Συγγραφείς: Acharya, Sampat1 (AUTHOR), Saldana, Shantall Cisneros1 (AUTHOR), Markus, Heike1 (AUTHOR) heike.markus@hof-university.de
Πηγή: Procedia Computer Science. 2026, Vol. 277, p1889-1898. 10p.
Θεματικοί όροι: Open source software, Packaging design, Data extraction, Image processing, Electronic data processing, Small business, Packaging industry, Digital transformation
Περίληψη: 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. [ABSTRACT FROM AUTHOR]
Βάση Δεδομένων: Supplemental Index
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  – Url: https://www.doi.org/10.1016/j.procs.2026.02.227?
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  Data: A Lightweight Open-Source Framework for Packaging Visualization and Data Automation.
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  Data: <searchLink fieldCode="JN" term="%22Procedia+Computer+Science%22">Procedia Computer Science</searchLink>. 2026, Vol. 277, p1889-1898. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Open+source+software%22">Open source software</searchLink><br /><searchLink fieldCode="DE" term="%22Packaging+design%22">Packaging design</searchLink><br /><searchLink fieldCode="DE" term="%22Data+extraction%22">Data extraction</searchLink><br /><searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Small+business%22">Small business</searchLink><br /><searchLink fieldCode="DE" term="%22Packaging+industry%22">Packaging industry</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+transformation%22">Digital transformation</searchLink>
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  Data: 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. [ABSTRACT FROM AUTHOR]
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      – SubjectFull: Data extraction
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              Text: 2026
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