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Reseach Article

An Approach towards Crop Management using DM and Image Processing

by Suraj Balwan, Ajinkya Kunjir, Mahesh Malwade
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 173 - Number 7
Year of Publication: 2017
Authors: Suraj Balwan, Ajinkya Kunjir, Mahesh Malwade
10.5120/ijca2017915359

Suraj Balwan, Ajinkya Kunjir, Mahesh Malwade . An Approach towards Crop Management using DM and Image Processing. International Journal of Computer Applications. 173, 7 ( Sep 2017), 18-22. DOI=10.5120/ijca2017915359

@article{ 10.5120/ijca2017915359,
author = { Suraj Balwan, Ajinkya Kunjir, Mahesh Malwade },
title = { An Approach towards Crop Management using DM and Image Processing },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2017 },
volume = { 173 },
number = { 7 },
month = { Sep },
year = { 2017 },
issn = { 0975-8887 },
pages = { 18-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume173/number7/28347-2017915359/ },
doi = { 10.5120/ijca2017915359 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:20:56.622521+05:30
%A Suraj Balwan
%A Ajinkya Kunjir
%A Mahesh Malwade
%T An Approach towards Crop Management using DM and Image Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 173
%N 7
%P 18-22
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The recent development and improvements in fields of computer science and technology has led to several innovations and inventions with the help of trending Algorithms, Domains, Techniques and tools. Data science is the domain of computer science comprising of Big Data and Data Mining, where Data Mining is the backbone of data science and has provided a base to Big Data which is now a trend in data science. Applications of Data Mining range from fields of Healthcare, Military, Aviation, Business systems and Agriculture. Agriculture, an application and area of data mining is a very recent research topics. Trending methods and techniques are nowadays able to produce and supply a large amount of data and knowledge on farming and agriculture activities, which can further be analysed in order to uncover some important matter out of it. The paper explains the proposed system which uses the combined technology of Data mining and Image processing. The data mining algorithms such as Random forest, Decision tree induction’s J48 and others are compared on a testing platform on basis of accuracy and other performance factors. Algorithm which outclasses the comparative study is selected for direct implementation in the system and its database. Image processing is used for identifying the crops, and process their image to forward it to further analysis. The crops will be classified by the Data Mining algorithms on basis of labels such as weak, strong, or mid-healthy. Data Mining and Image processing, technologies when combined together in one system can exploit the levels of parallelism and can achieve an enhanced faster rate of classification and processing. The records and tabular structure of the plants or agriculture data can be visualized using Data Mining Visualization techniques such as 2D/3D Graphs, Pie charts, tree graph etc.

References
  1. Ankita Dewan, Meghna Sharma , ”Prediction of Heart Disease Using a Hybrid Technique in Data Mining Classification” , 2015 2ndInternationalConference on Computing for Sustainable Global Development (INDIACom), IEEE 2015.
  2. Jyotshna Solanki, Prof. (Dr.) Yusuf Mulge, “Different Techniques used in Data Mining”,2015 International Journal of Advanced Research in Computer Science and Software Engineering.
  3. I. Jagielska, C. Mattehews, T. Whitfort, " A study in experimental evaluation of neural network and genetic algorithm techniques for knowledge acquisition in fuzzy classification systems, IEEE 2002.
  4. Tellaeche, A., BurgosArtizzu, X. P., Pajares, G., & Ribeiro, A. (2007), “A vision-based hybrid classifier for weeds detection in precision agriculture through the Bayesian and Fuzzy k-Means paradigms”, In Innovations in Hybrid Intelligent Systems (pp. 72-79). Springer Berlin Heidelberg
  5. K. Verheyen, D. Adriaens, M. Hermy, and S. Deckers, “High resolution continuous soil classification using morphological soil profile descriptions”, Geoderma, vol. 101, pp. 31-48, 2001.
  6. Veenadhari, S. 2007, “Crop productivity mapping based on decision tree and Bayesian classification”. Unpublished M.Tech Thesis submitted to Makhanlal Chaturvedi National University of Journalism and Communication, Bhopal.
  7. Ajinkya Kunjir, Harshal Sawant, Nuzhat F. Shaikh, “A Survey on Prediction of Multiple Diseases using Data Mining and Visualization Techniques”, IJCA December 2016.
  8. Wikispaces https//weka.wikispaces.com
  9. Prof. Navneet Goyal, “Data Mining Applications in Agriculture”, BITS PILANI.
  10. Dr. Dilip Roy Chowdhury, Subhashis Ojha, “An Emprical Study on Mushroom Disease Diagnosis : A Data Mining approach”, IRJET 2017.
Index Terms

Computer Science
Information Sciences

Keywords

Image Processing Image Recognition Data Mining Sensors Data Warehouse J48 Random Forest Visualization.