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Research Article | Open Access |

Performance Evaluation of E32 Long Range Radio Frequency 915 MHz based on Internet of Things and Micro Sensors Data

Author 1: Puput Dani Prasetyo Adi Author 2: Akio Kitagawa
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 10, No. 11 · Published 2019 · Cited by 35

DOI: https://doi.org/10.14569/IJACSA.2019.0101106

Abstract

This research discusses how to build and analyze a 915 MHz Long Range (LoRa) E32 Frequency-based Node Sensor network with a Micro Sensor with 3 sensor outputs produced i.e, Temperature (DegC), Air Pressure (hPa), and Humidity (%). therefore, This research succeeded in making a sensor node using the LoRa E32 915 MHz using a mini type ATmega 328p microcontroller with a 3.7 volt, 1000 mAh battery. The display on the receiver uses an 8X2 LCD which will output 3 sensor data outputs. furthermore, the result and analysis of this research are how to analysis of the LoRa Chirp Signal, furthermore, LoRa Chirp Signal obtained from the Textronix Spectrum analyzer in realtime, Quality of Service (QoS), Receive Signal Strength Indicator (RSSI) (-dBm), uplink and downlink data on the Internet Server. Furthermore, The Micro Sensor Graph Output will be displayed on the application server with a sensor data graph. In this research Application Server used is Thingspeak from Mathworks.

Keywords

How to Cite this Article

Adi, P. D. P., & Kitagawa, A. (2019). Performance Evaluation of E32 Long Range Radio Frequency 915 MHz based on Internet of Things and Micro Sensors Data. International Journal of Advanced Computer Science and Applications, 10(11). https://doi.org/10.14569/IJACSA.2019.0101106

Adi, Puput Dani Prasetyo, and Akio Kitagawa. "Performance Evaluation of E32 Long Range Radio Frequency 915 MHz based on Internet of Things and Micro Sensors Data." International Journal of Advanced Computer Science and Applications, vol. 10, no. 11, 2019, https://doi.org/10.14569/IJACSA.2019.0101106.

@article{Adi2019,
  title     = {Performance Evaluation of E32 Long Range Radio Frequency 915 MHz based on Internet of Things and Micro Sensors Data},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {11},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Puput Dani Prasetyo Adi and Akio Kitagawa},
  doi       = {10.14569/IJACSA.2019.0101106},
  url       = {https://doi.org/10.14569/IJACSA.2019.0101106}
}

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