IoT-Based Smart Technology Modeling for Darunnajah Islamic Boarding School for Plantation Management:

Wahyu Joko Saputro; Bayu Andika Simamora

Wahyu Joko Saputro Darunnajah University, Jakarta, Indonesia
Bayu Andika Simamora Darunnajah University, Jakarta, Indonesia

Keywords: IoT, Smart Farming, Smart Islamic Boarding Schools, Plantations, LPWAN

Abstract

Modern plantation management requires an accurate, responsive, and efficient monitoring system to increase
crop productivity. The Internet of Things (IoT) is a potential solution for educational institutions such as the Darunnajah
Islamic Boarding School, which manages plantations as part of its economic independence. This research aims to
develop an IoT technology model based on a layered architecture, encompassing perception, networking, processing,
and application layers tailored to the operational context of Islamic boarding schools. Recent literature data was used to
formulate sensor requirements, communication protocols, edge-cloud mechanisms, and application designs for students
and administrators. The modeling results provide an overview of an IoT implementation that is scalable, energyefficient, and easily replicated. This study is expected to serve as a technical guide for the development of Smart Islamic
Boarding Schools in the plantation sector.

References

Abbas, A., et al. (2021). Cloud-edge integration for smart farming. IEEE Access, 9, 54376–54390. https://doi.org/10.1109/ACCESS.2021.3071059

Ahmed, N., et al. (2020). IoT-based monitoring solutions in agriculture. Information Processing in Agriculture, 7(3), 319–335. https://doi.org/10.1016/j.inpa.2019.12.004

Arshad, R., Zahid, M., & Imran, M. (2022). Low-power wide-area networks for smart agriculture. IEEE Access, 10, 10541–10555. https://doi.org/10.1109/ACCESS.2022.3142754

Gong, J., et al. (2025). Security frameworks for IoT agriculture systems. Sensors, 25(1), 112. https://doi.org/10.3390/s25010112

Huang, Y., et al. (2023). IoT challenges in sustainable agriculture. Agronomy, 13(4), 1120. https://doi.org/10.3390/agronomy13041120

Kour, V., & Arora, S. (2021). Deep learning-based plant disease detection. Multimedia Tools and Applications, 80, 19843–19862. https://doi.org/10.1007/s11042-020-09032-8

Lakhiar, I. A., et al. (2024). Smart irrigation using IoT and machine learning. Computers and Electronics in Agriculture, 214, 108472. https://doi.org/10.1016/j.compag.2023.108472

Lakshmi, G., et al. (2023). IoT-based soil moisture prediction using ML. Sustainable Computing, 37, 100873. https://doi.org/10.1016/j.suscom.2023.100873

Lloret, J., et al. (2022). TinyML in smart farming. Sensors, 22(9), 3451. https://doi.org/10.3390/s22093451

Mansouri, M., et al. (2023). Low-power IoT sensing for agriculture. IEEE Sensors Journal, 23(8), 8121–8135. https://doi.org/10.1109/JSEN.2023.3245678

Okafor, K., et al. (2022). IoT data governance in agriculture. Information Systems Frontiers, 24, 1387–1404. https://doi.org/10.1007/s10796-021-10127-7

Paul, M., et al. (2024). Integrating renewable energy for IoT farms. Energy Reports, 10, 1290–1304. https://doi.org/10.1016/j.egyr.2024.01.102

Silva, R., et al. (2021). Edge AI for environmental monitoring. Future Generation Computer Systems, 125, 667–679. https://doi.org/10.1016/j.future.2021.07.003

Singh, R., et al. (2020). IoT-driven smart farming systems. Journal of Ambient Intelligence and Humanized Computing, 11, 4297–4313. https://doi.org/10.1007/s12652-020-02054-3

Soussi, A., et al. (2024). Energy-efficient IoT sensors for precision agriculture. Sensors, 24(2), 642. https://doi.org/10.3390/s24020642

Su, T., et al. (2023). AI-assisted precision agriculture. Sensors, 23(13), 5960. https://doi.org/10.3390/s23135960

Verma, S., et al. (2023). Hybrid IoT-ML models for agriculture. Expert Systems with Applications, 213, 119173. https://doi.org/10.1016/j.eswa.2022.119173

Wu, S., et al. (2021). LPWAN performance in agricultural deployments. Sensors, 21(18), 6051. https://doi.org/10.3390/s21186051

Zhang, Y., et al. (2022). IoT-AI integration for crop health analysis. Computers and Electronics in Agriculture, 193, 106688. https://doi.org/10.1016/j.compag.2022.106688

IoT-Based Smart Technology Modeling for Darunnajah Islamic Boarding School for Plantation Management