Crop, Fertilizer and Pesticide Recommendation using Ensemble Method and Sequential Convolutional Neural Network

Authors

  • Keerthi Ketheneni Assistant Professor, Department of Computer Science and Engineering, V R Siddhartha Engineering College, Vijayawada, A.P, India
  • Padma Yenuga Assistant Professor, Department of IT, PVP Siddhartha Institute of Technology, Vijayawada, A.P, India
  • Parimala Garnepudi Department of Computer Science and Engineering, VFSTR Deemed to be University, Vadlamudi, Guntur, India
  • Laksmikanth Paleti Associate Professor, Department of CSBS, RVR&JC Engineering College of Engineering, Guntur, A.P, India
  • Sesha Srinivas V. Associate Professor, Department of Computer Science and Engineering, RVR&JC Engineering College of Engineering, Guntur, A.P, India
  • Naga Raju Burla Assistant Professor, Department of Computer Science and Engineering (IOT), RVR&JC Engineering College of Engineering, Guntur, A.P, India
  • Srinivas O. Assistant Professor, Department of Computer Science and Engineering (AI&ML), RVR&JC Engineering College of Engineering, Guntur, A.P, India
  • Venkata Ramana Mancha Assistant Professor, Department of Computer Science and Engineering, GITAM Deemed to be University, Visakhapatnam, A.P. India
  • Srikanth Meda Associate Professor, Department of Computer Science and Engineering, RVR&JC Engineering College of Engineering, Guntur, India-522019
  • Narasimha Rao Yamarthi Professor, School of Computer Science and Engineering, VIT-AP University, Amaravati-522237, A.P, India.

Keywords:

Machine Learning, Recommendation System, K-nearest Neighbor(KNN), Support Vector Machine(SVM), Random Forest Algorithm, Sequential Convolutional Neural Network

Abstract

Agriculture is the backbone of the Indian economy, with 60% - 70% of the Indian people relying on agriculture for subsistence. Unfortunately, farmers sometimes don't have the time needed to carefully consider all important facts before making decisions. As a result, they rely on agricultural experts, who may or may not always be available. With the aid of precision agriculture, these farmers are given knowledge on the specific crops that should be grown on their property. The major objective is to develop a website which makes it simple to use by using the Machine Learning model to generate the real-time prediction that analyzes environmental and soil factors like Nitrogen (N), Potassium (K), Phosphorous (P), pH, Temperature, Humidity, Soil moisture and Rainfall which suggests the best crop to grow using Ensemble Model through Majority Voting Mechanism, fertilizer to apply using Fertilizer Dictionary and pesticide based on the image analysis of the pest using  Sequential Convolutional Neural Network(CNN) from Kaggle dataset. The resulting model when given inputs on the web interface recommends the crop suitable based on soil condition hence giving best decision on what crops to grow, what fertilizer to be used and helpful for identification of the pest and prescribe the appropriate dosage of pesticide.

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References

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Published

25.12.2023

How to Cite

Ketheneni, K. ., Yenuga, P. ., Garnepudi, P. ., Paleti, L. ., Srinivas V., S. ., Burla, N. R. ., O., S. ., Mancha, V. R. ., Meda, S. ., & Yamarthi, N. R. . (2023). Crop, Fertilizer and Pesticide Recommendation using Ensemble Method and Sequential Convolutional Neural Network. International Journal of Intelligent Systems and Applications in Engineering, 12(2), 473–485. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4292

Issue

Vol. 12 No. 2 (2024)

Section

Research Article

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