Bibliographische Detailangaben
| Titel: |
Real-time event-driven sensor data analytics at the edge-Internet of Things for smart personal healthcare. |
| Autoren: |
Ray, Partha Pratim, Dash, Dinesh, De, Debashis |
| Quelle: |
Journal of Supercomputing; Sep2020, Vol. 76 Issue 9, p6648-6668, 21p |
| Schlagwörter: |
SENSOR placement, DETECTORS, INTERNET of things, DATA analysis |
| Abstract: |
Real-time service has become a key for efficient serving of the Internet of Things (IoT)-based smart e-Healthcare. Several orientations have tried to pave this side of the technology but severely lacked in terms of incorporations of lightweight and open IoT-based frameworks. This study presents two different experiments that deals with the real-time visualization, charting and analytics while using real-time and open java script frameworks that includes Node.js, Johnny-Five, SperialPort, PubNub client, EON.js, Chart.js, Express Server and Socket.io. The objective of this work is to investigate the IoT-based real-time analytics behavior in cost-effective e-health sensor deployment scenario. The results found from the study advocates for the growth and assimilation of IoT-based open-source java script frameworks for serving real-time sensor data analytics in e-Healthcare sector. [ABSTRACT FROM AUTHOR] |
|
Copyright of Journal of Supercomputing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Datenbank: |
Complementary Index |
Full Text Finder 
Nájsť tento článok vo Web of Science