• Himanshu Attri
• Manjari S M
• Laxmi V

Agriculture is an important part of a country like India. Technologies such as artificial intelligence and machine learning play an important role in improving agriculture and food production while reducing waste and increasing agricultural productivity make the farm sustainable. Land allocation is a growing science in today’s world. Many studies have suggested different strategies to solve these problems , including data mining, statistics, and traditional learning methods. However, there are still many shortcomings in generating accurate classification results. Therefore, this proposed model is a new method for solving land allocation problems using deep learning to build good models. This document describes a model that provides deep learning solution for farmer and crop level small farms. According to the test results,The proposed model succeeded in classifying with 96.25% accuracy.

Soil Analysis, Image classification, Convolutional Neural Network, accuracy ,alexnet architecture

"A Deep Learning Model for Soil Detection and Crop Recommendation for Small Farmers", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.l437-l441, May-2023, Available :http://www.jetir.org/papers/JETIR2305B66.pdf

"A Deep Learning Model for Soil Detection and Crop Recommendation for Small Farmers", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppl437-l441, May-2023, Available at : http://www.jetir.org/papers/JETIR2305B66.pdf