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Pest Detection System

Harshil Rana1 , Reema Pandya2

Section:Research Paper, Product Type: Journal Paper
Volume-9 , Issue-12 , Page no. 23-25, Dec-2021

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v9i12.2325

Online published on Dec 31, 2021

Copyright © Harshil Rana, Reema Pandya . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Harshil Rana, Reema Pandya, “Pest Detection System,” International Journal of Computer Sciences and Engineering, Vol.9, Issue.12, pp.23-25, 2021.

MLA Style Citation: Harshil Rana, Reema Pandya "Pest Detection System." International Journal of Computer Sciences and Engineering 9.12 (2021): 23-25.

APA Style Citation: Harshil Rana, Reema Pandya, (2021). Pest Detection System. International Journal of Computer Sciences and Engineering, 9(12), 23-25.

BibTex Style Citation:
@article{Rana_2021,
author = {Harshil Rana, Reema Pandya},
title = {Pest Detection System},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2021},
volume = {9},
Issue = {12},
month = {12},
year = {2021},
issn = {2347-2693},
pages = {23-25},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5422},
doi = {https://doi.org/10.26438/ijcse/v9i12.2325}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v9i12.2325}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5422
TI - Pest Detection System
T2 - International Journal of Computer Sciences and Engineering
AU - Harshil Rana, Reema Pandya
PY - 2021
DA - 2021/12/31
PB - IJCSE, Indore, INDIA
SP - 23-25
IS - 12
VL - 9
SN - 2347-2693
ER -

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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.

Key-Words / Index Term

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

References

[1] D. Gondal, Y. Khan, “Early Pest Detection from Crop using Image Processing and Computational Intelligence”, FAST-NU Research Journal (FRJ), Volume 1, Issue 1, January 2015
[2] https://plantmethods.biomedcentral.com/articles/10.1186/s13007-019-0475-z
[3] https://assets.researchsquare.com/files/rs242641/v1/9584bc73-4d82-4f48-8474 aea00f7d704f.pdf?c=1631874347
[4] P. Ashok, J. Jayachandran, “Pest Detection and Identification by Applying Color Histogram and Contour Detection by Svm Model”, Volume 8, Issue 3S, February 2019
[5] L. Deng, Y. Wang, “Research on insect pest image detection and recognition based on bio-inspired methods”, Volume 169, Pages 139-148, May 2018
[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
[8] Aparajita Datta, “Classification of Agricultural Pests Using Statistical and Color Feature Extraction and Support Vector Machine”, IJCSE, Volume 7, Issue 1, Page no. 37-41, Jan 2019
[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