Jordanian Journal of Informatics and Computing

ISSN: 3080-6828 (Online)

A Cost-Effective Embedded Weather Monitoring System for Airport Air Traffic Control Applications

by 

Kamil Audah Kareem ;

Mahmood A. Al-Shareeda

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Published: 2026

Abstract

The weather has become an important factor for safe and effective airport ATC. Precise and minute-by-minute measurement of local meteorological parameters is a necessity, especially at the time of aircraft take-off and landing. In this paper, an inexpensive embedded weather monitoring system is proposed for air- port air traffic control applications. The developed system relies on an Arduino Uno microcontroller, which encompasses several environmental sensors to record the main parameters, such as temperature, relative humidity, precipitation, and wind speed. The system makes use of a DHT22 sensor to measure temperature and humidity, a rain sensor module that is used for detecting precipitation in the environment, and a custom-made infrared anemometer for estimating wind speed with pulse counting using interrupts. All the collected information is processed in real-time and shown on an I2C-driven LCD module, allowing on-spot situational awareness. It is hardware architecture aims at reducing cost, modularity, and easy deployment. Experimental tests in a real environment have proved the stabilization of the system and successfully collected data. The findings support the fact that our solution offers valid real-time weather information, which can be used as ancillary decision support in airport environments. Not intended to substitute certified meteorology stations, the service can still provide a useful and cost-effective alternative for small or regional airports, as well as educational and pilot club applications. Upcoming improvements are related to wireless communication, sensor calibration, and connection to established air traffic control systems.

Keywords

Embedded weather monitoringAirport air traffic controlEnvironmental sensingLow-cost embedded systemReal-time data acquisition

A Cost-Effective Embedded Weather Monitoring System for Airport Air Traffic Control Applications is licensed under CC BY 4.0CCBY

References

  1. Aditya, V., Aswin, D. S., Dhaneesh, S. V., Chakravarthy, S., Kumar, B. S., & Venkadavarahan, M. (2024). A review on air traffic flow management optimization: Trends, challenges, and future directions. Discover Sustainability, 5(1), 519. https://doi.org/10.1007/s43621-024-00519-9
  2. Almazroi, A. A., Alkinani, M. H., Al-Shareeda, M. A., & Manickam, S. (2024). A novel DDoS mitigation strategy in 5G-based vehicular networks using Chebyshev polynomials. Arabian Journal for Science and Engineering, 49(9), 11991–12004. https://doi.org/10.1007/s13369-024-08938-4
  3. Abdillah, R. E., Moenaf, H., Rasyid, L. F., Achmad, S., & Sutoyo, R. (2024). Implementation of artificial intelligence on air traffic control: A systematic literature review. In Proceedings of the 18th International Conference on Ubiquitous Information Management and Communication (IMCOM) (pp. 1–7). IEEE. https://doi.org/10.1109/IMCOM61040.2024.10460728
  4. Renkhoff, J., Ternus, S., & Guleria, Y. (2025). A survey on personalized conflict resolution approaches in air traffic control. Aerospace, 12(9), 751. https://doi.org/10.3390/aerospace12090751
  5. Alves, D., Belo-Pereira, M., Mendonça, F., & Morgado-Dias, F. (2025). Intelligent visibility forecasting at airports: A systematic review. Environmental Research Communications. Advance online publication. https://doi.org/10.1088/2515-7620/ad8c2b
  6. Ogunwole, O., Onukwulu, E. C., Joel, M. O., Adaga, E. M., & Ibeh, A. I. (2023). Modernizing legacy systems: A scalable approach to next-generation data architectures and seamless integration. International Journal of Multidisciplinary Research and Growth Evaluation, 4(1), 901–909.
  7. Mohammed, B. A., Al-Shareeda, M. A., Al-Mekhlafi, Z. G., Alshudukhi, J. S., & Al-Dhlan, K. A. (2024). HAFC: Handover authentication scheme based on fog computing for 5G-assisted vehicular blockchain networks. IEEE Access, 12, 6251–6261. https://doi.org/10.1109/ACCESS.2024.3350274
  8. Castruita-López, J. F., Aviles, M., Toledo-Pérez, D. C., Macías-Socarrás, I., & Rodríguez-Reséndiz, J. (2025). Electromyography signals in embedded systems: A review of processing and classification techniques. Biomimetics, 10(3), 166. https://doi.org/10.3390/biomimetics10030166
  9. Baker, B., Woods, J., Reed, M. J., & Afford, M. (2024). A survey of short-range wireless communication for ultra-low-power embedded systems. Journal of Low Power Electronics and Applications, 14(2), 27. https://doi.org/10.3390/jlpea14020027
  10. Soto-Cruz, J., Ruiz-Ibarra, E., Vázquez-Castillo, J., Espinoza-Ruiz, A., Castillo-Atoche, A., & Mass-Sanchez, J. (2024). A survey of efficient lightweight cryptography for power-constrained microcontrollers. Technologies, 13(1), 3. https://doi.org/10.3390/technologies13010003
  11. Thakur, D. S., Kourav, S., Shah, S. K., & Verma, K. (2024). Area- and speed-efficient Vedic RISC processors for embedded systems. In Proceedings of the IEEE 13th International Conference on Communication Systems and Network Technologies (CSNT) (pp. 1219–1224). IEEE. https://doi.org/10.1109/CSNT60226.2024.10521946
  12. Soni, M. S., Jisan, M., Kaustav, B., & Ghosh, R. (2025). Advancements in weather monitoring systems: A comprehensive review. In Proceedings of the 8th International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech) (pp. 1–5). IEEE.
  13. Ganesan, S., Lean, C. P., Chen, L., Yuan, K. F., Kiat, N. P., & Khan, M. R. B. (2024). IoT-enabled smart weather stations: Innovations, challenges, and future directions. Malaysian Journal of Science and Advanced Technology, 180–190.
  14. Kumar, A., Malhotra, S., Kaur, D. P., & Gupta, L. (2022). Weather monitoring and air quality prediction using machine learning. In Proceedings of the 1st International Conference on Computational Science and Technology (ICCST) (pp. 364–368). IEEE. https://doi.org/10.1109/ICCST55977.2022.10044413
  15. Ujoodha, M., Pultoo, A., & Oojorah, A. (2021). Climate monitoring using an Arduino-based mobile weather station and open-source codes. JESS: Journal of Education on Social Science, 16(1), 105–114.
  16. Mabrouki, J., Azrour, M., Dhiba, D., Farhaoui, Y., & El Hajjaji, S. (2021). IoT-based data logger for weather monitoring using Arduino-based wireless sensor networks with remote graphical application and alerts. Big Data Mining and Analytics, 4(1), 25–32. https://doi.org/10.26599/BDMA.2020.9020016
  17. Michailidis, I., Mountzouris, P., Triantis, P., Pagiatakis, G., Papadakis, A., & Dritsas, L. (2025). An Arduino-based, portable weather monitoring system remotely usable through the mobile telephony network. Electronics, 14(12), 2330. https://doi.org/10.3390/electronics14122330
  18. Venugopalaswamy, S., Sujitha, V. H. S. D., Padmavathi, G. L., Sravya, M., Jahnavi, D. D., & Panguluri, S. K. (2024). Dual-axis solar tracking system with weather monitoring system. International Journal of Engineering Technology and Management Sciences, 8(2), 88–99.
  19. Stoyanov, S., Kuzmanov, Z., & Stoyanova, T. (2024). Weather monitoring system using IoT-based DIY automatic weather station. In Proceedings of the 9th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE) (pp. 1–6). IEEE. https://doi.org/10.1109/EEAE60042.2024.10482317