STAP Journal of Security Risk Management

ISSN: 3080-9444 (Online)

Secure IoT-Based Smart Agriculture System Using Wireless Sensor Networks for Remote Environmental Monitoring

by 

Mahmood A. Al-Shareeda ;

Laith Badr Najm ;

Ali Ahmed Hassan ;

Sajjad Mushtaq ;

Hussein Abdul Ali

PDF logoPDF

Published: 2024/11/23

Abstract

Designing and implementing a secure IoT-based smart agriculture system that uses wireless sensor networks (WSNs) for real-time monitoring to keep the best environment and irrigates automatically. The proposed system is based on the ESP32 microcontroller and incorporates sensors for soil moisture, temperature, humidity, pH, and total dissolved solids (TDS), enabling precise agricultural resource management. The system is powered by solar energy to ensure continuous operation in remote areas or off the grid. Via Transport Layer Security (TLS), data is securely transmitted to the cloud, and device authentication is tokenized through Blynk IoT-a firm favorite among the Internet of Things community with its platform for control. You can control your irrigation and watch over the environment in real time with a mobile application, which means that a person needs only be present half of the time, avoiding waste for both water and electricity. Experimental results demonstrate a high accuracy in environment-sensing that leads to efficient water utilization, and stable, secure communication. The system is a low-cost, scalable solution for modernizing farming operations while addressing potential cybersecurity risks in an IoT agricultural environment.

Keywords

Smart AgricultureInternet of Things (IoT)Wireless Sensor Networks (WSN)ESP32TLSSecure CommunicationSoil Moisture MonitoringAutomated IrrigationBlynk IoTPrecision Farming.

Secure IoT-Based Smart Agriculture System Using Wireless Sensor Networks for Remote Environmental Monitoring is licensed under CC BY 4.0CCBY

References

  1. Saini, A. K., Yadav, A. K., et al. (2025). A comprehensive review on technological breakthroughs in precision agriculture: IoT and emerging data analytics. European Journal of Agronomy, 163, 127440.
  2. Al-Shareeda, M. A., Manickam, S., & Saare, M. A. (2022). Intelligent drone-based IoT technology for smart agriculture system. In 2022 International Conference on Data Science and Intelligent Computing (ICDSIC) (pp. 41–45). IEEE.
  3. Saikia, P., Sahu, B., Prasad, G., Kumar, S., Suman, S., & Kumar, K. (2025). Smart infrastructure systems: A review of IoT-enabled monitoring and automation in civil and agricultural engineering. Asian Journal of Research in Computer Science, 18(4), 24–44.
  4. Thilakarathne, N. N., Bakar, M. S. A., Abas, P. E., & Yassin, H. (2025). Internet of Things enabled smart agriculture: Current status, latest advancements, challenges and countermeasures. Heliyon, 11(3).
  5. Al-Shareeda, M. A., Manickam, S., Saare, M. A., & Arjuman, N. C. (2023). Proposed security mechanism for preventing fake router advertisement attack in IPv6 link-local network. Indonesian Journal of Electrical Engineering and Computer Science, 29, 518–526.
  6. Choudhary, V., Guha, P., Pau, G., & Mishra, S. (2025). An overview of smart agriculture using Internet of Things (IoT) and web services. Environmental and Sustainability Indicators, 100607.
  7. Nawaz, M., & Babar, M. I. K. (2025). IoT and AI for smart agriculture in resource-constrained environments: Challenges, opportunities and solutions. Discover Internet of Things, 5(1), 24.
  8. Hou, P. S., Fadzil, L. M., Manickam, S., & Al-Shareeda, M. A. (2023). Vector autoregression model-based forecasting of reference evapotranspiration in Malaysia. Sustainability, 15(4), 3675.
  9. Singh, H., Yadav, P., Rishiwal, V., Yadav, M., Tanwar, S., & Singh, O. (2025). Localization in WSN-assisted IoT networks using machine learning techniques for smart agriculture. International Journal of Communication Systems, 38(5), 6004.
  10. Dhar, S., & Bose, I. (2021). Securing IoT devices using zero trust and blockchain. Journal of Organizational Computing and Electronic Commerce, 31(1), 18–34.
  11. Almazroi, A. A., Alqarni, M. A., Al-Shareeda, M. A., Alkinani, M. H., Almazroey, A. A., & Gaber, T. (2024). FCA-VBN: Fog computing-based authentication scheme for 5G-assisted vehicular blockchain network. Internet of Things, 25, 101096.
  12. Kaur, B., Dadkhah, S., Shoeleh, F., Neto, E. C. P., Xiong, P., Iqbal, S., Lamontagne, P., Ray, S., & Ghorbani, A. A. (2023). Internet of Things (IoT) security dataset evolution: Challenges and future directions. Internet of Things, 22, 100780.
  13. Quy, V. K., Hau, N. V., Anh, D. V., Quy, N. M., Ban, N. T., Lanza, S., Randazzo, G., & Muzirafuti, A. (2022). IoT-enabled smart agriculture: Architecture, applications, and challenges. Applied Sciences, 12(7), 3396.
  14. Al-Shareeda, M. A., Ali, A. M., Hammoud, M. A., Kazem, Z. H. M., & Hussein, M. A. (2025). Secure IoT-based real-time water level monitoring system using ESP32 for critical infrastructure. Journal of Cyber Security and Risk Auditing, 2, 43–52.
  15. Singh, S. K., Azzaoui, A., Choo, K.-K. R., Yang, L. T., & Park, J. H. (2023). A comprehensive survey on blockchain for secure IoT-enabled smart city beyond 5G: Approaches, processes, challenges, and opportunities. Human-centric Computing and Information Sciences, 13, 51.
  16. Mazhar, N., Salleh, R., Zeeshan, M., & Hameed, M. M. (2021). Role of device identification and manufacturer usage description in IoT security: A survey. IEEE Access, 9, 41757–41786.
  17. Al-Shareeda, M. A., Alsadhan, A. A., Qasim, H. H., & Manickam, S. (2024). Software defined networking for Internet of Things: Review, techniques, challenges, and future directions. Bulletin of Electrical Engineering and Informatics, 13(1), 638–647.
  18. Imteaj, A., Thakker, U., Wang, S., Li, J., & Amini, M. H. (2021). A survey on federated learning for resource-constrained IoT devices. IEEE Internet of Things Journal, 9(1), 1–24.
  19. Hercog, D., Lerher, T., Truntić, M., & Težak, O. (2023). Design and implementation of ESP32-based IoT devices. Sensors, 23(15), 6739.
  20. Babun, L., Denney, K., Celik, Z. B., McDaniel, P., & Uluagac, A. S. (2021). A survey on IoT platforms: Communication, security, and privacy perspectives. Computer Networks, 192, 108040.
  21. Zijie, F., Al-Shareeda, M. A., Saare, M. A., Manickam, S., & Karuppayah, S. (2023). Wireless sensor networks in the Internet of Things: Review, techniques, challenges, and future directions. Indonesian Journal of Electrical Engineering and Computer Science, 31(2), 1190–1200.
  22. Athani, S., Tejeshwar, C., Patil, M. M., Patil, P., & Kulkarni, R. (2017). Soil moisture monitoring using IoT enabled Arduino sensors with neural networks for improving soil management for farmers and predict seasonal rainfall for planning future harvest in North Karnataka—India. In 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC) (pp. 43–48). IEEE.
  23. Sayanthan, S., Thiruvaran, T., & Kannan, N. (2018). Arduino based soil moisture analyzer as an effective way for irrigation scheduling. In 2018 IEEE International Conference on Information and Automation for Sustainability (ICIAfS) (pp. 1–4). IEEE.
  24. Bhadani, P., & Vashisht, V. (2019). Soil moisture, temperature and humidity measurement using Arduino. In 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (pp. 567–571). IEEE.
  25. Chew, K.-M., Tan, S. C.-W., Loh, G. C.-W., Bundan, N., & Yiiong, S.-P. (2020). IoT soil moisture monitoring and irrigation system development. In Proceedings of the 2020 9th International Conference on Software and Computer Applications (pp. 247–252).
  26. Hamoodi, S. A., Hamoodi, A. N., & Haydar, G. M. (2020). Automated irrigation system based on soil moisture using Arduino board. Bulletin of Electrical Engineering and Informatics, 9(3), 870–876.
  27. Mir, R. A., & Ishrat, M. (2020). Wide-area agricultural advanced monitoring and prediction system using IoT and machine learning. International Journal of Management (IJM), 11(8).
  28. Pramanik, M., Khanna, M., Singh, M., Singh, D., Sudhishri, S., Bhatia, A., & Ranjan, R. (2022). Automation of soil moisture sensor-based basin irrigation system. Smart Agricultural Technology, 2, 100032.
  29. Zhu, H.-H., Huang, Y.-X., Huang, H., Garg, A., Mei, G.-X., & Song, H.-H. (2022). Development and evaluation of Arduino-based automatic irrigation system for regulation of soil moisture. International Journal of Geosynthetics and Ground Engineering, 8(1), 13.
  30. Kaur, A., Bhatt, D. P., & Raja, L. (2024). Developing a hybrid irrigation system for smart agriculture using IoT sensors and machine learning in Sri Ganganagar, Rajasthan. Journal of Sensors, 2024(1), 6676907.
  31. Fernández Luque, J. E., Cuevas Sánchez, M., & Romero Vicente, R. (2023). Irrigating for sustainable intensive agriculture: Technological approaches.