Survey on Crop Recommendation System for KRISHI JAL APP


EOI: 10.11242/viva-tech.01.05.001

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Citation

Sakshi Shinde, Krupashree Sawant, Komal Shirsath, Akshata Raut, "Survey on Crop Recommendation System for KRISHI JAL APP", VIVA-IJRI Volume 1, Issue 6, Article 1, pp. 1-5, 2023. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

Agriculture is a paramount sector of the Indian economy as it contributes about 17% to the total GDP and provides employment to over 60% of the population. Agricultural commodities engendered must undergo a series of operations such as harvesting, threshing, winnowing, bagging, conveyance, storage, processing, and exchange before they reach the market, and as conspicuous from several studies across the country, there are considerable losses in crop output at all these stages. The main problems that are faced by Indian agriculture are uncertainty in the water supply, lack of remunerative income, and fragmentation of land holdings. After going through the previous research on the prediction of crops using different, machine learning models, its shortcoming was exposed. Previous research just considered the soil parameters and the weather conditions to predict the crops that must be planted on the farm. The proposed system not only considers the soil parameters but also water available for farming and then provides the output which takes all input and based on those parameters will provide the crops that have to be planted on the farm. The Model will work in two phases. In the first phase, extraction of information from the input will be done. In the second phase, the extracted information will be given as input to the trained machine learning model and then the recommendation of the crops will be displayed.

Keywords

Crops, Machine Learning Model, Phase, Parameters, Recommendation, Sundry

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