▷ FPGA Based Meteorological Monitoring Station

⭐⭐⭐⭐⭐ #FPGA Based Meteorological Monitoring Station from Victor Asanza

• ➡️ #DigitalSystems #DigitalElectronic #DigitalCircuits #HDL #VHDL #FPGA
• ➡️ 2021 IEEE Sensors Applications Symposium #SAS
• ➡️ Presented by: Víctor Asanza
• ⭐ Read full paper: https://ieeexplore.ieee.org/abstract/document/9530151
• ⭐ Source code repository: https://github.com/vasanza/Weather-Monitoring-Station
• ⭐ Dataset: https://dx.doi.org/10.21227/mdfs-ya42
• ➡️ When using this resource, please cite the original publication:
• V. Asanza, R. E. Pico, D. Torres, S. Santillan and J. Cadena, "FPGA Based Meteorological Monitoring Station," 2021 IEEE Sensors Applications Symposium (SAS), 2021, pp. 1-6, doi: 10.1109/SAS51076.2021.9530151.
• ✅ Abstract:
• In this paper, we propose to implement a meteorological monitoring station using embedded systems. This model is possible thanks to different sensors that enable us to measure several environmental parameters, such as i) relative humidity, ii) average ambient temperature, iii) soil humidity, iv) rain occurrence, and v) light intensity. The proposed system is based on a field-programmable gate array device (FPGA). The proposed design aims at ensuring high-resolution data acquisition and at predicting samples with precision and accuracy in real-time. To present the collected data, we develop also a web application with a simple and friendly user interface.

✅ Conference content:

• Introduction

• Related work

• Dataset

• Methodology

• Results

• Conclusions

• Published in

• For more information

✅ References:

1. X. H. V. Zambrano, A. C. Cedeno, J. M. Alava, J. M. Cedeno, E. K. Sinichenko and I. I. Gritsuk, "Mathematical model to determine the runoff coefficient based on precipitation and curve number data in the Manabi hydrographic demarcation Ecuador", Journal of Physics: Conference Series, vol. 1687, no. 1, pp. 012036, 2020, November.
2. K. Kaewwongsri and K. Silanon, "Design and implement of a weather monitoring station using CoAP on NB-IoT network", 2020 17th International Conference on Electrical Engineering/Electronics Computer Telecommunications and Information Technology (ECTI-CON), pp. 230-233, 2020, June.
3. Stefano Abbate, Marco Avvenuti, Luca Carturan and Daniel Cesarini, "Deploying a communicating automatic weather station on an alpine glacier. The 4th International Conference on Ambient Systems", Networks and Technologies the 3rd International Conference on Sustainable Energy Information Technology.
4. E. B. Beşikçi, T. Kececi, O. Arslan and O. Turan, "An application of fuzzy-AHP to ship operational energy efficiency measures", Ocean Engineering, vol. 121, pp. 392-402, 2016.
5. S. N. G. Rocha, A. Cristobal-Salas and N. I. L. Santes, "REMMA citizen observatory: a monitoring and an alerting real-time system", 2015 International Conference on Computing Systems and Telematics (ICCSAT), pp. 1-5, 2015, October.
6. M. Haefke, S. Mukhopadhyay and H. Ewald, "A Zigbee Based Smart Sensing Platform for Monitoring Environmental Parameters", IEEE Conference on Instrumentation and Measurement Technology, pp. 1-8.
7. G. R. Mendez, M. A. Yunus and S. C. Mukhopadhyay, "A Wi-Fi based Smart Wireless Sensor Network for an Agricultural Environment", Fifth International Conference on Sensing Technology, pp. 405-410.
8. I. Aziz, M. Hasan, M. Ismail, M. Mehat and N. Haron, "Remote Monitoring in Agricultural Greenhouse using Wireless Sensor and Short Message Service", International Journal of Engineering Technology, vol. 9, pp. 1-12.
9. M. Dinesh and P. Saravanam, "FPGA Based Real Time Monitoring System for Agricultural Field", International Journal of Electronics and Computer Science Engineering, pp. 1514-1519.
10. S. SHAARI et al., "FPGA-based artificial neural network for prediction of solar radiation data from sunshine duration and air temperature", 2008 IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering, pp. 118-123, 2008.
11. H. S. Jang, K. Y. Bae, H. S. Park and D. K. Sung, "Solar power prediction based on satellite images and support vector machine", IEEE Transactions on Sustainable Energy, vol. 7, no. 3, pp. 1255-1263, 2016.
12. V. A. Armijos, N. S. Chan, R. Saquicela and L. M. Lopez, "Monitoring of system memory usage embedded in FPGA", 2020 International Conference on Applied Electronics (AE), pp. 1-4, 2020.
13. V. Asanza, G. Sanchez, R. Cajo and E. Peláez, "Behavioral Signal Processing with Machine Learning Based on FPGA" in Systems and Information Sciences. ICCIS 2020. Advances in Intelligent Systems and Computing, Cham:Springer, vol. 1273, 2021.
14. Juan Cadena, Steven Santillan, Victor Asanza and Rebeca Estrada, "Weather Monitoring Station For Farms And Agriculture", IEEE Dataport, 2021, [online] Available: https://dx.doi.org/10.21227/mdfs-ya42.
15. T. Teranishi, Tera Term Open Source Project, December 2019, [online] Available: https://ttssh2.osdn.jp/index.html.en.
16. A. Neundorf, CuteCom, December 2019, [online] Available: http://cutecom.sourceforge.net/.

Read related topics

• ✅ 2021 Paper: Monitoring a turkey hatchery based on a #cyber_physical_system
• ✅ 2020 Paper: Behavioral Signal Processing with Machine Learning based on #FPGA
• ✅2020 Paper: Implementation Of Automated System For The Reservoir 66 of the Irrigation System Chambo Guano
• ✅ 2020 Paper: Monitoring of system memory usage embedded in #FPGA
• ➡️ https://github.com/vasanza/EmbeddedSystems
• ✅Artificial Intelligence #AI based on #FPGA
• ✅ Introduction to Embedded Systems
• ✅ Programming Embedded Systems
• ✅ 2021 PAO1: Proyectos Propuestos
• ➡️ Machine Learning #ML using #Matlab