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Digital packaging design method of intelligent products based on internet of things technology

Gangbing Song

International Journal of Manufacturing Technology and Management2025https://doi.org/10.1504/ijmtm.2025.144124article
AJG 1
Weight
0.37

What the paper says

Aiming at the problems of large feature extraction error of packaging image and poor packaging image design effect in the process of digital packaging design of intelligent products at this stage, this paper studies the digital packaging design method of intelligent products combined with internet of things technology. First, build a packaging data collection platform based on internet of things technology. Then, the digital packaging features of intelligent products are extracted by Harris corner feature method, combined with the digital filter to pre-treatment the packaging characteristics. Finally, the automatic packaging generation model is constructed by regularisation algorithm, and the model is optimised by maximising information entropy to realise the digital packaging design of intelligent products. The experimental results show that the minimum feature extraction error of the proposed method is 0.2%, and the maximum packaging colour enhancement is 95%, which can effectively reduce the extraction error and have a good digital packaging generation effect.

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https://doi.org/https://doi.org/10.1504/ijmtm.2025.144124

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@article{gangbing2025,
  title        = {{Digital packaging design method of intelligent products based on internet of things technology}},
  author       = {Gangbing Song},
  journal      = {International Journal of Manufacturing Technology and Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijmtm.2025.144124},
}

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Digital packaging design method of intelligent products based on internet of things technology

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.