ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume VI-4/W2-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-4/W2-2020, 41–45, 2020
https://doi.org/10.5194/isprs-annals-VI-4-W2-2020-41-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-4/W2-2020, 41–45, 2020
https://doi.org/10.5194/isprs-annals-VI-4-W2-2020-41-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  15 Sep 2020

15 Sep 2020

AN APPROACH ADOPTED FOR SMART DATA GENERATION AND VISUALIZATION PROBLEMS

C. Capodiferro1 and M. Mazzei2 C. Capodiferro and M. Mazzei
  • 1UTIU, Computer Engineering Faculty, 00186 Rome, Italy
  • 2CNR, Italian National Research Council - IASI, Institute of Systems Analysis and Computer Science, 00185 Rome, Italy

Keywords: IoT, Smart Data, Smart Services, WSN, LoRaWAN, TIG stack, Data Visualization

Abstract. This paper discusses how to address and overcome some of the problems related to smart data generation and visualization, such as the poor autonomy of wireless sensor devices and the flexibility of the data management platform. We described the implementation and field experiment of a modular IoT application for Smart-Farming, in which the sensor devices are powered by an on-board battery and the data management system is based on a highly flexible software stack, capable of displaying time series graphs and processing millions of data per second. The experiment shown that the power consumption of the sensor devices depends on many factors and that the lifecycle of the devices can reach years using ultra-low power processors, low power wide area network (LPWAN) such as LoRaWAN and a mix of energy saving techniques. The data management and visualization platform shown to be able to display many types of time-series graphs, deal with a wide variety of data-sources and effectively manage a large amount of data.