Time series analysis of clustering high dimensional data in precision agriculture

Author

Singh, Sweta ; Champawat, Kiran Singh ; Ambegaokar, Sanya ; Gupta, Animesh ; Sharma, Shirish

Author_Institution

IT Dept., MPSTME (NMIMS), Mumbai, India

fYear

2015

Firstpage

1

Lastpage

8

Abstract

Precision agriculture is widely being implemented with increase in technology demand and reduction in its cost. It is the application of latest technology to the agricultural field with the objective of maximizing production capacity. It is a practice of observing, analyzing and applying mined data to the inter and intra ground fluctuation of crops. The purpose of this research paper is to analyze and inspect the clustering of high dimensional data in precision agriculture. Various clustering techniques have been implemented with respect to its use in precision agriculture. And their respective advantages and disadvantages are listed as well.

Keywords

agriculture; cost reduction; data analysis; pattern clustering; time series; cost reduction; high dimensional data clustering; precision agriculture; technology demand; time series analysis; Agriculture; Clustering algorithms; Conferences; Correlation; Correlation coefficient; Speech recognition; Technological innovation; Moran´s I; agglomeration; fuzzy c-means; k-means; mean shift; pearson´s coefficient; precision agriculture;

fLanguage

English

Publisher

ieee

Conference_Titel

Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on

Conference_Location

Coimbatore

Print_ISBN

978-1-4799-6817-6

Type

conf

DOI

10.1109/ICIIECS.2015.7193192

Filename

7193192