A Robust analysis of Cloud Computing Framework with Machine Learning Intentions for Industrial Applications

Abstract

In this paper, a novel distributed computing structure is given machine learning (ML) calculations for aviation applications, for example, condition-based support, recognizing inconsistencies, foreseeing the beginning of part disappointments, and diminishing aggregate lifecycle costs. This cloud structure has been created by utilizing MapReduce, HBase, and Hadoop Distributed File System (HDFS) innovations on a Hadoop bunch of OpenSUSE Linux machines. Its ML calculations depend on Mahout ML Library and its online interface is fabricated utilizing JBoss and JDK. Essentially, the huge information from different Honeywell information sources are overseen by our HBase and broke down by different ML calculations. Clients can utilize this cloud based diagnostic toolset through internet browsers whenever and anyplace. More explanatory consequences of utilizing this structure will be distributed later.