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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM42171

Plant Disease Prediction and Farmers Assistance Using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM42171

Volume:

9 |

3 |

Mar 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM42171

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

DMS

Dr. M SENGALIAPPAN

MS

MADHAV S

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Abstract

Agriculture plays a crucial role in sustaining economies and food security worldwide. In the context of Digital India, leveraging technology for farming can significantly enhance efficiency and productivity. This paper presents a comprehensive agricultural application designed to assist farmers in multiple domains. The platform offers features such as plant and disease management, enabling early detection and mitigation of crop diseases to minimize economic losses. Additionally, a marketplace facilitates the buying and selling of farming equipment and tools, ensuring fair pricing and easy accessibility. Agent involvement ensures the seamless management of agricultural machinery, allowing direct communication for bookings and service ratings. Administrative functionalities provide real-time agricultural news and updates through notifications, keeping stakeholders informed. Furthermore, a reporting and feedback system allows users to report technical issues and provide insights for system improvements. By integrating these functionalities, the proposed platform enhances agricultural efficiency, streamlines equipment access, and promotes informed decision-making among farmers.

KEYWORDS

Plant Disease Detection CNN

Cite This Article

Dr. M SENGALIAPPAN, MADHAV S, "Plant Disease Prediction and Farmers Assistance Using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 3, Mar 2025. https://doi.org/10.55041/IJSREM42171

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Publication Date

7/2/2025

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Review Rounds: 2

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

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