Smart Crop Advisory for Small and Marginal Farmers

Agriculture remains a key way people survive across many rural areas where small farms dominate. Still, missing quick access to knowledge, expert tips, or new tools often leads to weak harvests and money troubles. A smart farming guide can offer custom advice using live data like what crops to grow, when to water, how to handle pests, or best fertilizer use. It pulls info from internet connected sensors, local weather trends, and ground checks to track field conditions as they change. By applying learning models, it builds flexible suggestions based on past patterns plus current surroundings. Farmers get local-language updates via phone or website, making it simple to use no matter their background. Because the system fits how people actually work, choices become smarter and more practical over time. As a result, growing food sustainably gets easier, which helps boost harvests without harming land. Over months, many small-scale growers see real gains in what they earn from farming.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-13
DOI
https://doi.org/10.5281/zenodo.19553882
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

Smart Crop Advisory for Small and Marginal Farmers

Sahithi Reddy P, S. Sugitha, Sneha P
Zenodo (CERN European Organization for Nuclear Research)
Smart Agriculture and AI
article

Smart Crop Advisory for Small and Marginal Farmers

Sahithi Reddy P, S. Sugitha, Sneha P
article en

Abstract

Agriculture remains a key way people survive across many rural areas where small farms dominate. Still, missing quick access to knowledge, expert tips, or new tools often leads to weak harvests and money troubles. A smart farming guide can offer custom advice using live data like what crops to grow, when to water, how to handle pests, or best fertilizer use. It pulls info from internet connected sensors, local weather trends, and ground checks to track field conditions as they change. By applying learning models, it builds flexible suggestions based on past patterns plus current surroundings. Farmers get local-language updates via phone or website, making it simple to use no matter their background. Because the system fits how people actually work, choices become smarter and more practical over time. As a result, growing food sustainably gets easier, which helps boost harvests without harming land. Over months, many small-scale growers see real gains in what they earn from farming.

Zenodo (CERN European Organization for Nuclear Research)
Zero hunger
Openalex Percentile: Top 7%
Smart Agriculture and AI
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