A Smart Farmland Advisory for Best Cropping Agricultural Practices Using Machine Learning

DOI

10.2991/978-94-6239-707-1_7How to use a DOI?

Keywords

Agro Advisory System; Plant Disease Detection; Image-Based Diagnosis; Soil Health Analysis; PlantVillage Dataset; Remote Sensing; Sustainable Farming; Decision Support System; AI in Agriculture

Abstract

Agricultural practice is the main business action of the preference of people. Crop production is a significant factor in agricultural practices, just as soil structure determines the suitability of crops. A major share of India’s GDP (Gross Domestic Product), directly or indirectly, comes from agricultural production. Most of India’s population still relies on agriculture or animal husbandry, providing a stable source of income. Thanks to the ample availability of natural solar energy, India boasts a diverse crop culture. Main farmers cultivate disjointed land and adapt rain-fed crops to traditional, repetitive cropping systems. To increase yields, farmers over apply fertilizers, leading to soil degradation. Instead of repetitive cropping, farmers should select appropriate crops adapted to the available environmental conditions. We Implemented rule-based system integrated with a machine learning techniques Such as Random Forest, Logistic Regression, Naive Bayes, SVM, Decision Tree, KNN and for image detection Convolutional Neural Networks(CNNs) provides dynamic, explainable crop recommendation using soil condition, environmental conditions, and past data trends. Users can view real-time sensor data.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Samir Mendhe
AU  - Ritesh Kumar
PY  - 2026
DA  - 2026/06/18
TI  - A Smart Farmland Advisory for Best Cropping Agricultural Practices Using Machine Learning
BT  - Proceedings of the International Conference on Recent Advances in Intelligent and Sustainable Technologies (RAIST 2026)
PB  - Atlantis Press
SP  - 70
EP  - 86
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-707-1_7
DO  - 10.2991/978-94-6239-707-1_7
ID  - Mendhe2026
ER  -