Soil Fertility Analysis and Crop Prediction using Machine Learning
Muneshwara M .S1, Abigail Angela Gracias2, C G Neha3, Preethi4, Akarsh S5
1Prof. Muneshwara M S*, Assistant Professor ,Dept. of CSE, BMS Institute of Technology & Management, Yelahanka, Bengaluru, Karnataka, India,.
2Ms.Abigail Angela Gracias2 , UG Student, Dept. of CSE, BMS Institute of Technology & Management, Yelahanka, Bengaluru, Karnataka, India.
3Ms. C G Neha, UG Student, Dept. of CSE, BMS Institute of Technology & Management, Yelahanka, Bengaluru, Karnataka, India.
4Ms. Preethi , UG Student, Dept. of CSE, BMS Institute of Technology & Management, Yelahanka, Bengaluru, Karnataka, India.
5Mr. Akarsh S , UG Student, Dept. of CSE, BMS Institute of Technology & Management, Yelahanka, Bengaluru, Karnataka, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 28, 2020. | Manuscript published on April 10, 2020. | PP: 380-383 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3609049620/2020©BEIESP | DOI: 10.35940/ijitee.F3609.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Through the exploitation of scientific knowledge and technology, man has made wonderous strides in the field of automation, the focus of which lies in ‘Robotics and Machine Learning’. All around us we see machines taking over work with accuracy and ease. Seen as a subset of artificial intelligence, machine learning relies on data, patterns in data and inference to aid technology in thinking for itself. This paper aims to apply the science of machine learning in the field of agriculture, by carrying soil fertility analysis using most accurate algorithm. The fertility of soil plays a principal role in determining the suitability of cultivating a particular crop on a given soil type. Analysis is carried out by the examination of various properties of the soil like the pH value, Electrical Conductivity, Moisture content, Temperature and (N)Nitrogen (P)Phosphorous (K) Potassium levels, followed up by soil type classification. Finally, a recommendation for the most suitable crop is provided in real time.
Keywords: Ensemble , k-nn, Machine Learning, Prediction, Random Forest, SV.
Scope of the Article: Artificial Intelligence and Machine Learning.