Pest Detection System

Authors

  • Rana H Computer Engineering, Sarvajanik College of Engineering and Technology, Gujarat Technological University, Surat, India
  • Pandya R Computer Engineering, Sarvajanik College of Engineering and Technology, Gujarat Technological University, Surat, India

DOI:

https://doi.org/10.26438/ijcse/v9i12.2325

Keywords:

Pests, Agriculture, Microscope, Endoscope, Insecticide, Pesticide, YOLO, Deep learning, Image Processing.

Abstract

Pests are organisms that spread diseases as well as causes destruction to the crops. Detection of pests is a must- do in the field of agriculture as growing plants to their fullest requires making the plant free from diseases. Although there are pesticides and insecticides available in the market, proper use of them and selection of them is a must to avoid excessive use or improper use of pesticide and insecticide. In this proposed system, pests are first attracted to a chemical named 1-Octen-3-ol above which flypaper is placed which will trap the small insects after which those insect gets detected using a USB digital microscope endoscope magnifier video camera and YOLO real-time object detection algorithm. The experiment has shown accurate results and might be a useful solution for preventing pests from destroying crops.

References

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[3] https://assets.researchsquare.com/files/rs242641/v1/9584bc73-4d82-4f48-8474 aea00f7d704f.pdf?c=1631874347

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[6] Faithpraise Fina, “AUTOMATIC PLANT PEST DETECTION AND RECOGNITION USING k-MEANS CLUSTERING ALGORITHM AND CORRESPONDENCE FILTERS”, IJABR, Vol 4, Issue 2, 2013, pp 189-199

[7] Jun Lui, “Tomato Disease and Pest Detection based on Improved YOLO V3 CNN”, Frontiers, 16 June 2020

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[9] D. Sindhu, “Image Processing Technology Application for Early Detection and Classification of Plant Diseases”, IJCSE, Volume 7, Issue 5, Page no. 92-97, May 2019

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Published

2021-12-31
CITATION
DOI: 10.26438/ijcse/v9i12.2325
Published: 2021-12-31

How to Cite

[1]
H. Rana and R. Pandya, “Pest Detection System”, Int. J. Comp. Sci. Eng., vol. 9, no. 12, pp. 23–25, Dec. 2021.

Issue

Vol. 9 No. 12 (2021): IJCSE December Edition

Section

Research Article

License

Creative Commons License

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