Big Data Environment for Agricultural Soil Analysis from CT Digital Images
In precision agriculture an increase of data and information has been observed and new approaches to improve knowledge are now required. Therefore, studies on Big Data are being conducted to find innovative solutions as a means to analyze large data sets. In this work, we present a Big Data environment for agricultural soil analysis from computed tomography (CT) images. Our structure is planned in three layers: source, Big Data environment, and applications. We use Hadoop framework in the second layer to process CT images and discuss how the 3D reconstruction is performed. Another application in the structure is the statistical analysis of soil samples. The Big Data environment is developed as a soil analysis system to gain an understand of the problems related to agricultural lands.
2016 IEEE Tenth International Conference on Semantic Computing (ICSC)