Development of IoT and WSN-Based Smart AgroWeather with Zigbee for Microclimate Management in Large-Scale Plantations

Authors

  • Made Santo Gitakarma Universitas Pendidikan Ganesha
  • Luh Putu Ary Sri Tjahyanti Universitas Panji Sakti
  • Gede Indrawan Universitas Pendidikan Ganesha
  • Ketut Udy Ariawan Universitas Pendidikan Ganesha
  • Wayan Mahardika Prasetya Wiratama Universitas Pendidikan Ganesha
  • Putu Aditya Pratama Universitas Panji Sakti
  • Putu Shantiawan Prabawa Universitas Panji Sakti

DOI:

https://doi.org/10.55927/fjst.v4i10.274

Keywords:

Internet of Things, Wireless Sensor Network, Smart AgroWeather, ZigBee, Microclimate Management

Abstract

This study develops and evaluates the Smart AgroWeather system, an IoT and WSN-based microclimate monitoring platform using ZigBee communication for large-scale plantations. Applying the Waterfall method, the system integrates sensors for temperature, humidity, air pressure, rainfall, and wind speed via a ZigBee mesh network connected to a Raspberry Pi gateway and cloud storage. Field testing on a 12-hectare dragon fruit plantation in Bulian, Bali showed a 95% data transmission success rate, low latency (20–25 ms), and stable power use (3.2–3.3 V). Integration with Google Cloud improved data accessibility and decision-making. The results confirm that IoT-WSN integration with ZigBee provides a scalable, energy-efficient, and sustainable solution for precision agriculture, supporting both theoretical advancement and practical application in smart farming.

References

Al-Karaki, J. N., & Kamal, A. E. (2004). Routing techniques in wireless sensor networks: A survey. IEEE Wireless Communications, 11(6), 6–28.

Alvarez, J., & Gomez, R. (2024). Cloud computing and big data analytics in smart agriculture: A review of emerging trends. Computers and Electronics in Agriculture, 216, 109859.

Amin, R., & Patel, D. (2024). Energy-efficient wireless sensor architecture for tropical precision agriculture. IEEE Access, 12, 55689–55704.

Berg Insight. (2025). IoT connectivity trends in agriculture 2025 report. Berg Insight AB.

Bidai, Z., Maimour, M., & Haffaf, H. (2012). Multipath extension of the ZigBee tree routing in cluster-tree wireless sensor networks. International Journal of Mobile Computing and Multimedia Communications, 4(2), 30–48.

Blokhin, Y. I., & Blokhina, S. Y. (2024). Hybrid wireless sensor networks for agricultural monitoring using ZigBee, WiFi, and LTE. Sensors and Actuators A: Physical, 368, 115490.

Dhivya, S., Jayanthi, N., & Valluvan, K. R. (2018). Enhancement of dual-hop layered LEACH routing protocol with mobility in wireless sensor networks. International Journal of Science and Engineering Science, 2(3), 46–50.

Farooq, M. O., Dogar, A. B., & Shah, G. A. (2010). MR-LEACH: Multi-hop routing with low energy adaptive clustering hierarchy. In Proceedings of the 4th International Conference on Sensor Technologies and Applications (pp. 262–268). IEEE.

Gao, Y., & Shen, X. (2022). Sustainable smart farming through IoT: A systematic review. Journal of Cleaner Production, 378, 134545.

Gao, Y., & Singh, A. (2023). Digital transformation in agriculture: IoT, cloud, and machine learning integration. Computers and Electronics in Agriculture, 210, 107651.

Ge, Y., Nan, Y., & Chen, Y. (2020). Maximizing information transmission for energy harvesting sensor networks by an uneven clustering protocol and energy management. KSII Transactions on Internet and Information Systems, 14(4), 1419–1436.

Gitakarma, M. S., Priyambodo, T. K., Suyanto, Y., & Sumiharto, R. (2020). Architectures, frameworks, and applications in IoT-based smart environment: A review. In International Conference on Vocational Education and Technology (pp. 1–9).

Gitakarma, M. S., Priyambodo, T. K., Suyanto, Y., & Sumiharto, R. (2021). A proposed multi-hop dynamic multi-zone LEACH protocol to extend network lifetime in wireless sensor network. In International Conference on Innovation in Science and Technology (pp. 54–61).

Gitakarma, M. S., Priyambodo, T. K., Suyanto, Y., & Sumiharto, R. (2024). Performance of multi-hop dynamic multi-zone for LEACH in wireless sensor network mapping on the agriculture area. ICIC Express Letters, 18(5), 443–453.

Gubernur Bali. (2019). Peraturan Daerah Provinsi Bali No. 8 Tahun 2019 tentang Sistem Pertanian Organik. Pemerintah Provinsi Bali.

Gubernur Bali. (2021). Peraturan Gubernur Bali No. 15 Tahun 2021 tentang Pelaksanaan Peraturan Daerah Nomor 8 Tahun 2019 tentang Sistem Pertanian Organik. Pemerintah Provinsi Bali.

Guerrero-Osuna, H. A., Luque-Vega, L. F., Carlos-Mancilla, M. A., Ornelas-Vargas, G., Castañeda-Miranda, V. H., & Carrasco-Navarro, R. (2021). Implementation of a MEIoT weather station with exogenous disturbance input. Sensors, 21(5), 1653.

Hu, Q., & Fernandes, J. (2022). Energy performance comparison of ZigBee and Wi-Fi protocols in smart agricultural monitoring. IEEE Access, 10, 91506–91518.

Ioannou, K., Karampatzakis, D., Amanatidis, P., Aggelopoulos, V., & Karmiris, I. (2021). Low-cost automatic weather stations in the Internet of Things. Information, 12(4), 146.

Karunathilake, E. M. B. M., Le, T., Heo, J., Chung, J., & Mansoor, S. (2023). Emerging IoT technologies for smart farming systems: Opportunities and innovations. Sensors, 23(14), 6520.

Kochlán, M., Hodon, M., & Cechovic, L. (2014). WSN for traffic monitoring using Raspberry Pi board. In Proceedings of the Federated Conference on Computer Science and Information Systems (pp. 1023–1026).

Koubâa, A., Alves, M., & Tovar, E. (2006). Modeling and worst-case dimensioning of cluster-tree wireless sensor networks. In Proceedings of the 27th IEEE International Real-Time Systems Symposium (pp. 1–10).

Lee, J. Y., Jung, K. D., Moon, S. J., & Jeong, H. Y. (2016). Improvement on LEACH protocol of a wide-area wireless sensor network. Multimedia Tools and Applications, 76(19), 19843–19860.

Li, P., & Cheng, Y. (2023). Dynamic clustering energy-efficient routing algorithm for precision agriculture sensor networks. Ad Hoc Networks, 146, 103007.

Nguyen, T. H., & Zhao, L. (2023). Robust environmental monitoring in IoT-based agriculture systems. Sensors and Actuators B: Chemical, 389, 133875.

Otieno, M. (2023). Smart agriculture systems and IoT security challenges. IEEE Internet of Things Journal, 10(18), 16483–16495.

Pathak, H. S., Brown, P., & Best, T. (2019). A systematic literature review of the factors affecting the precision agriculture adoption process. Precision Agriculture, 20(6), 1292–1316.

Rahman, M. M., & O’Neill, J. (2021). Impact of weather interference on ZigBee network reliability for agricultural IoT applications. Sensors, 21(8), 2764.

Rao Jaladi, A., Khithani, K., Pawar, P., Malvi, K., & Sahoo, G. (2017). Environmental monitoring using wireless sensor networks (WSN) based on IoT. International Research Journal of Engineering and Technology, 4(1), 1371–1378.

Saini, A., & Singh, N. (2024). Comparative analysis of low-power wireless communication protocols for IoT agriculture. International Journal of Communication Systems, 37(2), e5321.

Saminathan, A. G., & Ponnuchamy, T. (2015). EE-LEACH: Development of energy-efficient LEACH protocol for data gathering in WSN. EURASIP Journal on Wireless Communications and Networking, 2015(1), 76.

Santos, V., Almeida, R., & Costa, J. (2021). Adaptive microclimate sensors for IoT-enabled smart agriculture. IEEE Sensors Journal, 21(20), 22563–22575.

Singh, S. K., Singh, M. P., & Singh, D. K. (2010). Routing protocols in wireless sensor networks: A survey. International Journal of Computer Science and Engineering Survey, 1(2), 63–83.

Sun, J., Wang, Z., Wang, H., & Zhang, X. (2007). Research on routing protocols based on ZigBee network. In Proceedings of the 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing (pp. 639–642). IEEE.

Tang, R., Aridas, C., & Abu Talip, M. (2023). Energy-efficient ZigBee routing for smart greenhouse networks. Journal of Network and Computer Applications, 218, 103650.

Tang, R., Wu, S., Tan, G., Guan, Y., Aridas, C., & Abu Talip, M. (2025). ZIRRA: ZigBee immune routing repair algorithm for wireless agricultural sensor networks. Computers and Electronics in Agriculture, 212, 108267.

Virnodkar, S. S., Pachghare, V. K., Patil, V. C., & Jha, S. K. (2020). Remote sensing and machine learning for crop water stress determination in various crops: A critical review. Precision Agriculture, 21(5), 1121–1155.

Wu, H., Han, Z., Zhu, J., Chen, Y., & Yang, F. (2022). Low-latency opportunistic routing for agricultural wireless sensor networks. IEEE Sensors Journal, 22(18), 17850–17863.

Zhang, L., Chen, H., & Wang, D. (2023). Hybrid wireless networks for large-scale agricultural monitoring. Journal of Ambient Intelligence and Humanized Computing, 14(6), 6453–6468.

Zhao, J., Erdogan, A. T., & Arslan, T. (2005). A novel application-specific network protocol for wireless sensor networks. In IEEE International Symposium on Circuits and Systems (pp. 5894–5897). IEEE.

Zuchriadi, A., Rahayu, F., Anggraeni, S., Razi, M. A., Oktaviandri, M., & Irga, I. (2023). Agricultural monitoring system using ESP32 microcontroller with IoT-based LoRa transmission. Journal Mantik, 7(2), 625–633.

Published

2025-10-31