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IEEE Transactions on Industrial Informatics
Article . 2019 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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An Innovative Methodology for Big Data Visualization for Telemedicine

Authors: Galletta, Antonino; Carnevale, Lorenzo; Bramanti, Alessia; Fazio, Maria;

An Innovative Methodology for Big Data Visualization for Telemedicine

Abstract

With the explosion of Big Data, visualizing statistical data became a challenging topic that has involved many research efforts over the last years. Interpreting Big Data and efficiently showing information for good understanding are difficult tasks, especially in healthcare scenarios, where different types of data have to been managed and cross-related. Some models and techniques for health data visualization have been presented in literature. However, they do not satisfy the visualization needs of physicians and medical personnel. In this paper, we present a new graphical tool for the visualization of health data, that can be easily used for monitoring health status of patients remotely. The tool is very user friendly, and allows physician to quickly understand the current status of a person by looking at colored circles. From a technical point of view, the proposed solution adopts the geoJSON standard to classify data into different circles.

Keywords

Big Data; cloud computing; data visualization; Geo javascript object notation (GeoJSON); Internet of Things (IoT); telemedicine; Control and Systems Engineering; Information Systems; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic Engineering, Big Data; cloud computing; data visualization; Geo javascript object notation (GeoJSON); Internet of Things (IoT); telemedicine

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
35
Top 10%
Top 10%
Top 10%
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