Abstract
The Internet of Things (IoT) is a growing technology that allows digital devices to be integrated into the network. The use of IoT technology makes it possible to collect information from various Global Navigation Satellite System (GNSS) receivers connected to the Internet, providing a unique opportunity to obtain information on spatial and temporal distribution. In this article, the ionospheric monitoring system is implemented using ThingSpeak (IoT). Ionospheric signal delay/Total Electronic Content (TEC) data from GNSS stations, Koneru Lakshmaiah Education Foundation (KLEF)—Guntur (16.44° N, 80.62° E, geographical), Port Blair (11, 43° N, 92,43° E)—geographical, Bengaluru (13,02° N, 77,57° E; geographical), Lucknow (26,76° N, 80,88° E; geographical) are used for analysis during the 2015 period. The ionospheric signal delays are computed from the ThingSpeak and the ionospheric TEC analysis are performed directly in the MATLAB software. The computed observed TEC values were compared to the IRI-16 (International Reference Ionosphere) model values. The standard deviation of the observed TEC for four GNSS stations is 17.26 TECU for Port Blair, 18.34 TECU for Bengaluru, 16.51 TECU for KLEF-Guntur and 14.07 TECU for Lucknow. The corresponding standard deviation of the IRI model is 11.38 TECU for Port Blair, 13.25 TECU for Bengaluru, 17.67 TECU for KLEF-Guntur and 15.66 TECU for Lucknow. As a result, the cloud-based monitoring system reduces operating costs, backs up and retrieves data. It optimizes productivity and collaboration around the world via the Internet.
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Acknowledgements
This research work was supported by Department of Science and Technology (DST)-FIST, New Delhi, India, vide sanction letter No: FIST sanction Order No. SR/FST/ETI-410/2016(C).
The authors are thankful to IGS and IRI working group for providing online data access, Dr. Gopi. S for providing GPS -TEC analysis software.
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Dabbakuti, J.R.K.K., Ch, B. Ionospheric monitoring system based on the Internet of Things with ThingSpeak. Astrophys Space Sci 364, 137 (2019). https://doi.org/10.1007/s10509-019-3630-0
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DOI: https://doi.org/10.1007/s10509-019-3630-0