A comprehension of rational in the computational aptitudes towards precision agriculture Murali E1,*, Anouncia S Margret2 1Research Scholar, VIT University, Vellore, Tamilnadu, India 2Professor, SCOPE, VIT University, Vellore, Tamilnadu, India *Corresponding Author: E. Murali Research Scholar(SCOPE), VIT university, Vellore, Tamilnadu Email: emurali88@gmail.com
Online published on 16 October, 2018. Abstract Precision agriculture is implementation of information technology in the field of agriculture. It is site specific agriculture where sensors are placed in the field to collect data. Usually, the data is acquired from sensors with the help of satellite. The collected sensor data is further processed to handle precise decision in the field of agriculture. The domain uses satellite images, sensor data and utilizes Information Technology to manage the concept based on observations, measurements and response. To do so, it follows either predictive approach of analysis or control approach of analysis. The predictive approach deals with the static indicators while the control approach focuses on the monitoring the entire cycle with adaptability to the need. With the advent of information technology, variety of intricacies has been introduced in the field of agriculture. Consequently, data mining becomes very much essential to provide suitable data sources for decision making. Lot of mining approaches has been attempted in the past towards delineating this agricultural data. Each of the methodologies possesses certain credentials as well as limitations. This paper attempts to highlight the rational of these data mining approaches towards helping precision agriculture as an effective endeavor. Top Keywords Precision agriculture, Sensor data, Data mining. Top |