Smart Farming Prediction Using Machine Learning
S. R. Rajeswari1, Parth Khunteta2, Subham Kumar3, Amrit Raj Singh4, Vaibhav Pandey5
1Parth Khunteta, Department of CSE, SRM University, Chennai (Tamil Nadu), India.
2Subham Kumar, Department of CSE, SRM University, Chennai (Tamil Nadu), India.
3Amrit Raj Singh, Department of CSE, SRM University, Chennai (Tamil Nadu), India.
4Vaibhav Pandey, Department of CSE, SRM University, Chennai (Tamil Nadu), India.
5MrsS. R. Rajeswari, Department of CSE, AP, ME, SRM University, Chennai (Tamil Nadu), India.
Manuscript received on 01 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 190-194 | Volume-8 Issue-7, May 2019 | Retrieval Number: G5110058719/19©BEIESP
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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: Agriculture is one of the major game changer and a major revenue producing sector in India. Different seasons, market and Biological Patterns influence the crop production ,but because of changes in these patterns result in an excellent loss to farmers .This factors can be minimized by using a suitable approach related to the knowledge of soil types ,pressure ,suitable weather, crop type. whereas, weather and crop types and be predicated using useful dataset that can aid to farmers by predicting the maximized profitable crops to grow. These paper mainly focus on the algorithms used to predict crop yield ,crop cost prediction. With the help of all these features smart farming can be achieved.
Keyword: Smart Farming, Big data , Neural network ,Dataset, Clustering, Farmbots, Farm drones, Machine Learning in Agriculture.
Scope of the Article: Machine Learning.