Analisis Sistem Aplkasi Pengolahan Citra Pada Pertanian Cerdas Untuk Pemantauan Tanaman

Authors

  • Supiyandi Supiyandi Universitas Pembangunan Panca Budi
  • Mona Donaon Universitas Islam Negeri Sumatera Utara
  • Muhammad Yusuf Azmi Universitas Islam Negeri Sumatera Utara

DOI:

https://doi.org/10.59841/saber.v2i3.1443

Keywords:

image processing, smart farming, crop monitoring, Convolutional Neural Networks, pest and disease detection, image segmentation, sustainable agriculture

Abstract

Smart farming has become a rapidly growing research area with the aim of increasing agricultural productivity and efficiency through advanced technologies. One of the key technologies in smart agriculture is image processing, which enables real-time monitoring and analysis of crop conditions. This article reviews image processing applications in smart agriculture, with a focus on the methods and techniques used for crop monitoring. Image processing methods discussed include pest and disease detection, measuring plant growth, as well as monitoring soil moisture and plant health. Image processing techniques such as convolution-based image analysis (Convolutional Neural Networks/CNNs), image segmentation, and pattern recognition are applied to obtain accurate and relevant information. Case studies and field experiments show that image processing can provide accurate and real-time data, enabling farmers to make more informed and efficient decisions. In conclusion, the application of image processing technology in smart agriculture has great potential to increase crop yields, reduce resource use, and advance sustainable agricultural practices.

References

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Gonzalez, R.C.dan Richard, E.W. (2004). Digital Image Processing with Matlab. Addison Wesley. UK.

Jayas, D.S., Paliwal, J., dan Visen, N.S. (2000). Multi-layer neural networks for image analysis of agricultural products. Journal of Agricultural Engineering Resources 77: 119-128.

Mayer, G.E. dan Neto, C. (2008). Verification of color vegetation indices for automated crop imaging applications. Computer and Electronics in Agriculture 63: 282-293.

Morimoto, T., Hatao, K. dan Hashimoto, Y. (1996). Intelligent control for plant production. Journal of Control Engineering Practice 4: 773-784.

Published

2024-07-02

How to Cite

Supiyandi Supiyandi, Mona Donaon, & Muhammad Yusuf Azmi. (2024). Analisis Sistem Aplkasi Pengolahan Citra Pada Pertanian Cerdas Untuk Pemantauan Tanaman . SABER : Jurnal Teknik Informatika, Sains Dan Ilmu Komunikasi, 2(3), 221–228. https://doi.org/10.59841/saber.v2i3.1443

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