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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM50363
Volume:
9 |
6 |
Jun 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
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.
As the primary source of income for most Indians, agriculture is a major economic sector in the country. With machine learning (ML) techniques, Harvestify aims to improve farming practices. This research includes the development of a machine learning (ML) system that assists farmers in predicting the optimal harvest times and recommending crops that are suitable for the soil and climate of their area. It also detects and treats plant issues using photo recognition. Harvestify also includes a Soil-depending Profiling System that analyzes data to select crops depending on soil characteristics and rainfall patterns. It suggests using the appropriate fertilizers to build better soil and boost agricultural yields. The system can identify sick leaves and provide treatment recommendations by utilizing machine learning algorithms such as Random Forest and convolutional neural networks. Plant disease detection is an important task. The incorporation of these technologies could lead to improved agricultural resilience, sustainability, and production for millions of Indian farmers.
KEYWORDS
Publication Date
6/15/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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