Pest Detection and Obliteration Based Robotic System

Authors

  • Pushpaveni H P Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bangalore, India
  • Manjunatha N Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bangalore, India
  • Hemalatha N J Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bangalore, India
  • Mahammedansar Y Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bangalore, India
  • Lalhriatpuii Lalhriatpuii Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bangalore, India

Keywords:

Image processing, Threshold, Pesticides, Intelligence, Microcontroller

Abstract

Agriculture is the back bone of the country and the growth of any country’s economy is directly dependent and proportional on the agricultural produce of that country. Hence, it becomes extremely important to safeguard and assist farmers in every way possible to help them achieve an excellent yield. In a technological aspect, this can be achieved by devising different instruments which can help the farmer to plough lands, sow seeds or even help him to keep an eye on the farm in his absence to spot intruders, insects or even rodents. This paper surveys one such aspect of utilizing technology for farms and that, is to detect pests.

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References

Muhammad Danish Gondal1 , Yasir Niaz Khan, “Early Pest Detection from Crop using Image Processing and Computational Intelligence”, FAST-NU Research Journal (FRJ), Pakistan, 2015, pp 59-68

Yan Li, Chunlei Xia and Jangmyung Lee, ” Vision-based Pest Detection and Automatic Spray of Greenhouse Plant”, IEEE International Symposium on Industrial Electronics, Korea, 2009,pp 920-925

Martin, “Identification and Counting of Pests using Extended Region Grow Algorithm”, 2nd International Conference on Electronics and Communication Systems,2015,pp 213-220

P. Rajesh Kanna and R. Vikram, “Agricultural Robot – A pesticide spraying device”, International Journal of Future Generation Communication and Networking,2020, pp. 150-160,

H. A. Hiary. B. Ahmad. M. Reyalat. M. Braik. (2011, Mar.). Fast and accurate detection and classification of plant diseases. International Journal of Computer Applications. 17(1), pp 31- 38.

B. S. Anami. J. D. Pujari. R. Yakkundinath. (2011, Sep). Identification and classification of normal and affected agriculture / horticulture produce based on combined color and texture feature extraction. International Journal of Computer Applications in Engineering Sciences. 1(3), pp.356-360.

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Published

2021-06-25

How to Cite

[1]
P. H P, M. N, H. N J, M. Y, and L. Lalhriatpuii, “Pest Detection and Obliteration Based Robotic System”, pices, pp. 18-19, Jun. 2021.

Issue

2021: PiCES - Special Issue

Section

Articles

License

Copyright (c) 2021 Perspectives in Communication, Embedded-systems and Signal-processing - PiCES

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