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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM34069

WEB BASED SOLUTION TO IDENTIFY AND SOLVE DISEASE IN PLANTS/CROPS

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM34069

Volume:

8 |

5 |

May 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM34069

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

RZ

Rasheeq Zehra

OS

Omkar Sharma

V

Vinayak

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Abstract

Dedicated to the welfare of Indian farmers, this research unveils ‘Green Doctor,’ a groundbreaking web-based solution aimed at combating plant diseases in India’s agricultural sector. Leveraging MobileNet Convolutional Neural Network (CNN), Green Doctor promises swift and precise disease identification in plants and crops. Through a robust methodology utilizing Indian plant disease datasets and a streamlined CNN architecture, this solution offers a beacon of hope for farmers. Results showcase the efficacy of rapid disease detection, facilitating timely intervention to mitigate crop losses and bolster agricultural productivity. Positioned as a free and user-friendly tool, Green Doctor embodies accessibility, speed, and contextual relevance, serving as a tribute to the Indian farming community. By reducing pesticide reliance, enhancing product quality, and bolstering farmer income, Green Doctor paves the path towards sustainable agriculture while enlightening stakeholders about plant diseases.

KEYWORDS

Plant diseases Web-based solution MobileNet CNN Disease detection Agricultural productivity Sustainable agriculture.

Cite This Article

Rasheeq Zehra, Omkar Sharma, Vinayak, "WEB BASED SOLUTION TO IDENTIFY AND SOLVE DISEASE IN PLANTS/CROPS," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 5, May 2024. https://doi.org/10.55041/IJSREM34069

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Publication Date

12/31/45426

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Double-Blind Peer Review

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The authors declare no conflict of interest related to this research work.

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