A Big Data Architecture For Heterogeneous Data In Precision Agriculture

Abstract

The increase in human population has triggered the need to increase the agriculture production worldwide. At the same time climatic conditions, water scarcity and population growth are decreasing the arable land. Hence there is a need to evolve novel ways to improve agricultural produce while utilizing lesser resources. Precision Agriculture combines temporal, spatial, remote, and individual data along with decisions to enable specific automated actions on fields. Big Data is one of the central technologies used in precision farming to store, retrieve and process abstract information. In the article we propose a system, method to efficiently collate, store and process data from multiple sources on a Big Data system and validate the approach. The proposed system will build on the Hadoop framework. © 2022 IEEE.