This paper is published in Volume-4, Issue-3, 2018
Area
Big Data
Author
Nikhil Chandra P
Co-authors
Nikhil U, Manjunath C R, Sahana Shetty
Org/Univ
School of Engineering and Technology Jain University (SET JU), Bengaluru, Karnataka, India
Pub. Date
07 May, 2018
Paper ID
V4I3-1313
Publisher
Keywords
Big data, Linear regression, Moisture content, pH, Weather.

Citationsacebook

IEEE
Nikhil Chandra P, Nikhil U, Manjunath C R, Sahana Shetty. Big data analytics in precision agriculture and constant monitoring of soil and weather, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Nikhil Chandra P, Nikhil U, Manjunath C R, Sahana Shetty (2018). Big data analytics in precision agriculture and constant monitoring of soil and weather. International Journal of Advance Research, Ideas and Innovations in Technology, 4(3) www.IJARIIT.com.

MLA
Nikhil Chandra P, Nikhil U, Manjunath C R, Sahana Shetty. "Big data analytics in precision agriculture and constant monitoring of soil and weather." International Journal of Advance Research, Ideas and Innovations in Technology 4.3 (2018). www.IJARIIT.com.

Abstract

Agriculture has been one of the zones where innovation has not been utilized to the fullest and the usage of Precision Agriculture (PA) is still in its beginning times. One of the most important parameters in the field of agriculture that needs to be monitored constantly is the moisture content of the soil. To maximize the productivity in this field the condition and development of the crops are the most critical variables and these elements rely upon the levels of moisture content in the soil. Different crops need different levels of moisture content, therefore it is very important to monitor and forecasts it. In this paper, a mathematical model is created to compute the surface soil dampness by utilizing both precipitation and evaporation rate obtained by the electromagnetic sensors installed in the ground. Evaporation can be considered to be a linear combination of dynamic evaporation and thermodynamic evaporation which happens due to radiation. Soil moisture content is inversely proportional to the evaporation rate and it is directly proportional to the precipitation rate. Therefore a linear regression model is the best fit to determine the soil moisture content. Constant monitoring can be made possible by the soil mapping software with the sensors which keep reading the data periodically.
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