Authors :
Sai Anand P; Sandeep S; V Pranav Srinivas; Rajeshwari G.L
Volume/Issue :
Volume 6 - 2021, Issue 7 - July
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/3kt4Zua
Abstract :
In India, Agriculture is very important and
practised broadly across the country. This industry plays
a major economic role in the country's development. So,
three main criteria are needed to be considered while
growing crops. Choosing fertilizers, selecting proper
crops according to the region’s climatic condition and
Knowledge of crop price are the criteria that benefit the
farmers and also helps the economic growth of the
country. This paper proposes three different models for
each of the above-mentioned criteria. The first model is
the Fertilizer predictor, which predicts the suitable
fertilizer that can be used for the given soil constituents.
The second model is the crop predictor, which predicts
the three most likely growable crops based on the given
climatic conditions. The third model is the future crop
price predictor, which predicts the crop price in future
based on past trends and prices.
Keywords :
Crop Management, Machine Learning, Data Visualization, KNN, ARIMA, Random Forest, Logistic Regression.
In India, Agriculture is very important and
practised broadly across the country. This industry plays
a major economic role in the country's development. So,
three main criteria are needed to be considered while
growing crops. Choosing fertilizers, selecting proper
crops according to the region’s climatic condition and
Knowledge of crop price are the criteria that benefit the
farmers and also helps the economic growth of the
country. This paper proposes three different models for
each of the above-mentioned criteria. The first model is
the Fertilizer predictor, which predicts the suitable
fertilizer that can be used for the given soil constituents.
The second model is the crop predictor, which predicts
the three most likely growable crops based on the given
climatic conditions. The third model is the future crop
price predictor, which predicts the crop price in future
based on past trends and prices.
Keywords :
Crop Management, Machine Learning, Data Visualization, KNN, ARIMA, Random Forest, Logistic Regression.