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Analysis Study Research Paper | Agriculture | India | Volume 11 Issue 3, March 2022
Generalized Smart Agriculture System with the Prediction of Crop Yield Per Year
Priyanka Mehta [2] | Niprojit Ghosh | Deepjyoti Chakraborty | Oindrila Ganguly | Vedatrayee Chakraborty
Abstract: Agriculture is one of the most essential and widely practiced occupations in India and it also plays a vital role in the development of our country [1]. Around 60 percent of the total land in this country is used for agriculture to meet the needs of 1.2 billion people, so improving crop prediction is therefore seen as a significant aspect of agriculture. Basically if one has a piece of land, she or he needs to know what kind of crop can be grown in this area [2, 3]. Agriculture also depends on various soil properties. Production of crops is also a difficult task since it involves factors like soil type, temperature, humidity etc. If it is possible to find the crop before sowing it, it would be of great help to the farmers and the other people involved to make appropriate decisions on the storage and business side [4-6]. The proposed project would solve agricultural problems by monitoring the agricultural area on the basis of soil properties and recommending the most appropriate crops to farmers, thereby helping them to significantly increase the crop productivity. In this work, the modelling makes use of different Machine Learning Techniques such that it gives the information which includes soil ingredients, rainfall, quantity of crops, production of crops with respect to temperature of that area etc. which would definitely be beneficial for the farmers.
Keywords: Machine Learning, Crop prediction, Rainfall prediction, soil ingredients, Crop recommendation
Edition: Volume 11 Issue 3, March 2022,
Pages: 933 - 938