Open AccessBig data analytics with graphical techniques applied on sensors data
Author(s) -
M. L. Oroian-Boca
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/591/1/012063
Subject(s) - big data , computer science , variety (cybernetics) , data science , analytics , process (computing) , state (computer science) , data analysis , data mining , artificial intelligence , algorithm , operating system
The term “Big Data” is now a popular way to refer to massive digital information available in both structured and unstructured form integrated from multiple, diverse, dynamic sources of information. Big data can be used to solve a variety of problems with significant cost reduction cost. Analysis and processing of large data sets represent a significant challenge. Massive data sets are collected and studied in numerous domains, from engineering sciences to social networks, biomolecular research, commerce, and security. Extracting valuable information from big data requires innovative approaches that efficiently process large amounts of data as well as handle and, moreover, utilize their big data analytics structure can be used in electronics industry too. In this study, I created a graphic tool in LabVIEW for the analyses of ECG signals for 3 types of subjects, in the same environment take in case the age of each subject and the influence of the environment on the physiological state of each one. The environmental conditions varied and the variations in the human body have been assessed in three situations: studying with music, studying without music and in relaxing state. LabVIEW proved to be an efficient tool to analyse and compare the produced signals in various time spans and also to compare the ECG signals for the investigated subjects.