Towards Big Data Solutions for Industrial Tomography Data Processing

Abstract

This paper presents an overview of what Big Data can bring to the modern industry. Through following the history of contemporary Big Data frameworks the authors observe that the tools available have reached sufficient maturity so as to be usable in an industrial setting. The authors propose the concept of a system for collecting, organising, processing and analysing experimental data obtained from measurements with process tomography. Process tomography is used for noninvasive flow monitoring and data acquisition. The measurement data is collected, stored and processed to identify process regimes and process threats. Further general examples of solutions that aim to take advantage of the existence of such tools are presented as proof of viability of such approach. As the first step in the process of creating the proposed system, a scalable, distributed, containerisation-based cluster has been constructed, with consumer-grade hardware.

An IoT based Condition Monitoring System of Biogas Electrical Generator for Performance Evaluation

“…Variety of the data from a number of machines acquired over a long duration can provide comprehensive understanding of the machines. However, efficient data management with scalability, high security and privacy needs to be taken into account [10,11].…”