Prototype of a Coffee Bean Weight Measuring Device Using a Webcam with the Convolutional Neural Network (CNN) Method at Roetin Coffee Shop

Authors

  • Nurul Budi Universitas Negeri Yogyakarta, Indonesia
  • Faris Yusuf Baktiar Universitas Negeri Yogyakarta, Indonesia

DOI:

https://doi.org/10.21831/jraee.v4i1.2375

Keywords:

CNN, Image Processing, Mobile Net, Coffee Beans

Abstract

The advancement of Artificial Intelligence (AI) and Computer Vision has enabled new opportunities for automation within the coffee industry, particularly in weight measurement of coffee beans, which is still performed manually and becomes inefficient at large scale. This study proposes an automatic weight estimation system using images captured by a webcam and processed through a Convolutional Neural Network (CNN) employing MobileNet as a lightweight regression model. The developed system analyzes visual features to estimate weight autonomously, offering an efficient, contactless alternative to conventional weighing tools and supporting stock monitoring for coffee industries and small enterprises.

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References

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Published

2026-08-31

How to Cite

Budi, N., & Faris Yusuf Baktiar. (2026). Prototype of a Coffee Bean Weight Measuring Device Using a Webcam with the Convolutional Neural Network (CNN) Method at Roetin Coffee Shop. Journal of Robotics, Automation, and Electronics Engineering, 4(1), 237–249. https://doi.org/10.21831/jraee.v4i1.2375

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