Secure IoT-Based Smart Agriculture System Using Wireless Sensor Networks for Remote Environmental Monitoring
dr Mahmood A. Al-Shareeda ;
mr Laith Badr Najm ;
mr Ali Ahmed Hassan ;
mr Sajjad Mushtaq ;
mr Hussein Abdul Ali
Published:
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
How to Cite the Article
Secure IoT-Based Smart Agriculture System Using Wireless Sensor Networks for Remote Environmental Monitoring is licensed under CC BY 4.0
References
- 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.
- Itoo, S., Khan, A. A., Ahmad, M., & Idrisi, M. J. (2023). A secure and privacy-preserving lightweight authentication and key exchange algorithm for smart agriculture monitoring system. IEEE Access, 11, 56875-56890.
- 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.
- Dhar, S., & Bose, I. (2021). Securing IoT devices using zero trust and blockchain. Journal of Organizational Computing and Electronic Commerce, 31(1), 18–34.
- 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.
- 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.
- 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.
- 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.
- 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.
- Hercog, D., Lerher, T., Truntić, M., & Težak, O. (2023). Design and implementation of ESP32-based IoT devices. Sensors, 23(15), 6739.
- 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.
- Deepa, R., Sankar, M., Sankari, C., & Kalaivani, R. (2023, January). IoT based energy efficient using wireless sensor network application to smart agriculture. In 2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT) (pp. 90-95). IEEE.
- 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.
- 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.
- 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.
- 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).
- 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.
- Vangala, A., Das, A. K., Chamola, V., Korotaev, V., & Rodrigues, J. J. (2023). Security in IoT-enabled smart agriculture: Architecture, security solutions and challenges. Cluster Computing, 26(2), 879-902.
- 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.
- 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.
- Fernández Luque, J. E., Cuevas Sánchez, M., & Romero Vicente, R. (2023). Irrigating for sustainable intensive agriculture: Technological approaches.