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Research Article | Open Access |

Performance Evaluation of Raspberry Pi as an IoT Edge Signal Processing Device for a Real-time Flash Flood Forecasting System

Author 1: Aslinda Hassan Author 2: Haniza Nahar Author 3: Wahidah Md Shah Author 4: Azlianor Abd-Aziz Author 5: Sarah Afiqah Sahiran Author 6: Nazrulazhar Bahaman Author 7: Mohd Riduan Ahmad Author 8: Isredza Rahmi A. Hamid Author 9: Muhammad Abu Bakar Sidik
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 13, No. 10 · Published 2022 · Cited by 7

DOI: 10.14569/IJACSA.2022.01310100

Abstract

The Raspberry Pi has evolved in recent years into a popular, low-cost, tiny computer for a wide range of IoT applications. Raspberry Pi is not only successful for data collection but also for data processing, including data storage and analysis. Thus, this study investigates the capability of Raspberry Pi as an edge processing device for capturing lightning strike signals in predicting flash flood locations. An electric and magnetic sensor (EMS) is connected to a Raspberry Pi in the experiment setup. The Raspberry Pi is then used to process digitised lightning signals. From the experiment, Raspberry Pi’s performance is measured using the performance metrics: central processing unit (CPU) usage and temperature. The results revealed that the Raspberry Pi could handle the real-time collection and processing of lightning signals from the EMSs without affecting the hardware capability.

Keywords

How to Cite this Article

Hassan, A., Nahar, H., Shah, W. M., Abd-Aziz, A., Sahiran, S. A., Bahaman, N., Ahmad, M. R., Hamid, I. R. A., & Sidik, M. A. B. (2022). Performance Evaluation of Raspberry Pi as an IoT Edge Signal Processing Device for a Real-time Flash Flood Forecasting System. International Journal of Advanced Computer Science and Applications, 13(10). https://doi.org/10.14569/IJACSA.2022.01310100

Hassan, Aslinda, et al.. "Performance Evaluation of Raspberry Pi as an IoT Edge Signal Processing Device for a Real-time Flash Flood Forecasting System." International Journal of Advanced Computer Science and Applications, vol. 13, no. 10, 2022, https://doi.org/10.14569/IJACSA.2022.01310100.

@article{Hassan2022,
  title     = {Performance Evaluation of Raspberry Pi as an IoT Edge Signal Processing Device for a Real-time Flash Flood Forecasting System},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {10},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Aslinda Hassan and Haniza Nahar and Wahidah Md Shah and Azlianor Abd-Aziz and Sarah Afiqah Sahiran and Nazrulazhar Bahaman and Mohd Riduan Ahmad and Isredza Rahmi A. Hamid and Muhammad Abu Bakar Sidik},
  doi       = {10.14569/IJACSA.2022.01310100},
  url       = {https://doi.org/10.14569/IJACSA.2022.01310100}
}

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