Design and Implementation of a Multi-Zone Automatic Irrigation Control System Based on Sugeno Fuzzy Logic for a Melon Seedling Incubator

  • Ahmad Fauzan Electrical Engineering Study Program, Faculty of Engineering, Universitas Singaper bangsa Karawang, Indonesia
  • Reni Rahmadewi Electrical Engineering Study Program, Faculty of Engineering, Universitas Singaper bangsa Karawang, Indonesia
Keywords: Capacitive Moisture Sensor, Irrigation Control, Melon Seedling, Normalized Moisture Index, Sugeno Fuzzy Logic

Abstract

Maintaining appropriate moisture conditions is important for the early growth of melon seedlings. This study developed a zone-based irrigation control system using six capacitive moisture sensors, an Arduino Mega 2560, one water pump, and three solenoid valves. The six seedling trays were divided into three irrigation zones, with the lower value of two sensors used to represent each zone condition. Each sensor was calibrated individually, and the analog readings were converted into a dimensionless Normalized Moisture Index (NMI). A zero-order Sugeno fuzzy inference system was used to determine irrigation duration based on four input conditions: Very Dry, Dry, Moist, and Wet. Lower NMI values produced longer irrigation durations, while wet conditions produced no irrigation command. The developed system was able to process sensor readings, calculate zone conditions, generate irrigation-duration outputs, and control the pump and solenoid valves according to the designed logic. The system demonstrates the application of capacitive sensing and Sugeno fuzzy control for irrigation management in melon seedlings.

References

Abdelmoneim, A. A., Al Kalaany, C. M., Dragonetti, G., Derardja, B., & Khadra, R. (2025). Comparative analysis of soil moisture-and weather-based irrigation scheduling for drip-irrigated lettuce using low-cost internet of things capacitive sensors. Sensors, 25(5), 1568. https://doi.org/10.3390/s25051568

Abdullah, U. H., Keumalasari, S., Yana, D., & Aufa, P. N. (2026). Correlation Analysis of Cocopeat Planting Media with Plant Height, Stem Diameter, and Number of Leaves of Oil Palm Plants (Elaeis guineensis Jacq). Biotropika: Journal of Tropical Biology, 14(2), 154-160. https://doi.org/10.21776/ub.biotropika.2026.014.02.06

Akhter, T., Muzamil, M., Rashid, S., Bashir, A., Singh, H., Malik, S., & Banday, R. U. Z. (2026). Impact of Compaction on Soil Properties, Plant Growth and Yield Potential: A Critical Approach for Sustainable Crop Production System. Transactions of the Indian National Academy of Engineering, 1-14. https://doi.org/10.1007/s41403-026-00576-4

Al-Shammary, A. A. G., Al-Shihmani, L. S. S., Fernández-Gálvez, J., & Caballero-Calvo, A. (2025). A comprehensive review of impacts of soil management practices and climate adaptation strategies on soil thermal conductivity in agricultural soils. Reviews in Environmental Science and Bio/Technology, 24(2), 513-543. https://doi.org/10.1007/s11157-025-09730-w

Aziz, A., Putratama, G. A., & Widiarto, W. (2025, December). Design and Implementation of an IoT-Driven Automatic Drip Irrigation and Fertilization System for Cocopeat-Based Greenhouse Farming. In 2025 9th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) (pp. 353-357). IEEE. https://doi.org/10.1007/s40030-024-00857-7

Borankulova, G., Altybayev, G., Tungatarova, A., Yeraliyeva, B., Dulatbayeva, S., Murzakhmetov, A., & Bekbolatov, S. (2025). Development of real-time water-level monitoring system for agriculture. Sensors, 25(17), 5564. https://doi.org/10.3390/s25175564

Bwambale, E., Abagale, F. K., & Anornu, G. K. (2022). Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review. Agricultural Water Management, 260, 107324. https://doi.org/10.1016/j.agwat.2021.107324

Costa, J. M., Egipto, R., Aguiar, F. C., Marques, P., Nogales, A., & Madeira, M. (2023). The role of soil temperature in mediterranean vineyards in a climate change context. Frontiers in Plant Science, 14, 1145137. https://doi.org/10.3389/fpls.2023.1145137

Dadlani, M., Gupta, A., Sinha, S. N., & Kavali, R. (2023). Seed storage and packaging. Seed Science and Technology, Springer, 239-266. https://doi.org/10.1007/978-981-19-5888-5_11

Ebstu, E. T., Hatiye, S. D., Goshime, D. W., Dingemanse, J. D., Dugassa, D. D., Fitensa, T., ... & Demeke, Y. G. (2026). Development and Testing of a Low‐Cost Soil Moisture Sensor for Real‐Time Irrigation Scheduling. Irrigation and Drainage, 75(1), 173-187. https://doi.org/10.1002/ird.70026

Grossnickle, S. C., & Ivetić, V. (2022). Root system development and field establishment: effect of seedling quality. New Forests, 53(6), 1021-1067. https://doi.org/10.1007/s11056-022-09916-y

Han, S., Kim, W., Lee, H. J., Joyce, R., & Lee, J. (2022). Continuous and real-time measurement of plant water potential using an AAO-based capacitive humidity sensor for irrigation control. ACS Applied Electronic Materials, 4(12), 5922-5932. https://doi.org/10.1021/acsaelm.3c00060

Helmy, H. S., Abuarab, M. E., Abdeldaym, E. A., Abdelaziz, S. M., Abdelbaset, M. M., Dewedar, O. M., ... & Mokhtar, A. (2025). Field-grown lettuce production optimized through precision irrigation water management using soil moisture-based capacitance sensors and biodegradable soil mulching. Irrigation Science, 43(5), 1045-1070. https://doi.org/10.1007/s00271-024-00969-9

Lan, R., Shen, W., Yao, W., Chen, J., Chen, X., & Yang, H. (2023). Bioinspired humidity-responsive liquid crystalline materials: from adaptive soft actuators to visualized sensors and detectors. Materials Horizons, 10(8), 2824-2844. https://doi.org/10.1039/D3MH00392B

Liang, M., Chen, L., Chen, G., Zhao, Y., Liu, G., Sun, E., ... & Qu, P. (2025). Protective effects of straw mulching on soil health and function: a review. Environmental Pollutants and Bioavailability, 37(1), 2533900. https://doi.org/10.1080/26395940.2025.2533900

Lim, J., Allen, K. S., Powning, C. B., & Harper, R. W. (2025). Impact of planting depth on urban tree health and survival. Forests, 16(12), 1788. https://doi.org/10.3390/f16121788

Liu, X., Zhao, Z., & Rezaeipanah, A. (2025). Intelligent and automatic irrigation system based on internet of things using fuzzy control technology. Scientific Reports, 15(1), 14577. https://doi.org/10.1038/s41598-025-98137-2

Liu, X., Zhao, Z., & Rezaeipanah, A. (2025). Intelligent and automatic irrigation system based on internet of things using fuzzy control technology. Scientific Reports, 15(1), 14577. https://doi.org/10.1038/s41598-025-98137-2

Liu, Y., & Yang, Y. (2023). Spatial-temporal variability pattern of multi-depth soil moisture jointly driven by climatic and human factors in China. Journal of Hydrology, 619, 129313. https://doi.org/10.1016/j.jhydrol.2023.129313

Liu, Y., Yang, Y., & Song, J. (2023). Variations in global soil moisture during the past decades: climate or human causes?. Water Resources Research, 59(7), e2023WR034915. https://doi.org/10.1029/2023WR034915

Liu, Z., Li, Z., Wang, C., Tian, Y., Han, Q., Wan, X., ... & Liu, G. (2026). Morphological, physiological, and root metabolomic responses of Hemerocallis minor Mill. to drought stress. Frontiers in Plant Science, 17, 1855949. https://doi.org/10.3389/fpls.2026.1855949

Madu, H., Yakubu, J., & Ahmad, U. (2026). A Mamdani Fuzzy Inference System for Intelligent Greenhouse Climate Control: Integrating Temperature, Humidity, and Soil Moisture for Adaptive Precision Agricultural Decision-Making. Nigerian Journal of Operations Research, 3(3), 41-61. https://doi.org/10.67868/cvvkx809

Morchid, A., Jebabra, R., Alami, R. E., Charqi, M., & Boukili, B. (2024, May). Smart agriculture for sustainability: the implementation of smart irrigation using real-time embedded system technology. In 2024 4th International conference on innovative research in applied science, engineering and technology (IRASET) (pp. 1-6). IEEE. https://doi.org/10.1109/IRASET60544.2024.10548972

Narkhede, H. I., Deokar, B. K., Kardile, D. S., Handore, A. V., & Surana, A. R. (2025). Cocopeat Biofilters: A sustainable approach for water purification and nutrient management. Separation and Purification Technology, 353, 128558. https://doi.org/10.1016/j.seppur.2024.128558

Nsoh, B., Katimbo, A., Guo, H., Heeren, D. M., Nakabuye, H. N., Qiao, X., ... & Kiraga, S. (2024). Internet of things-based automated solutions utilizing machine learning for smart and real-time irrigation management: A review. Sensors, 24(23), 7480. https://doi.org/10.3390/s24237480

Pahlawan, R., Nasution, B. B., & Fahmi, F. (2025, September). Soil Moisture Control Algorithm Using MQTT and Fuzzy Logic for Enhancing Agricultural Productivity. In 2025 International Conference on Computing and Applied Informatics (ICCAI) (pp. 1-6). IEEE. https://doi.org/10.1109/ICCAI65301.2025.11278957

Pramanik, M., Khanna, M., Singh, M., Singh, D. K., Sudhishri, S., Bhatia, A., & Ranjan, R. (2022). Automation of soil moisture sensor-based basin irrigation system. Smart Agricultural Technology, 2, 100032. https://doi.org/10.1016/j.atech.2021.100032

Ramakrishnan, T., Shameer, M. S., Prasath, A. M., Hemnath, R., Rathinam, S. C., & Avinasilingam, M. (2024, October). Automatic plant irrigation system. In AIP Conference Proceedings (Vol. 3221, No. 1, p. 030004). AIP Publishing LLC.

Rasheed, M. W., Tang, J., Sarwar, A., Shah, S., Saddique, N., Khan, M. U., ... & Sultan, M. (2022). Soil moisture measuring techniques and factors affecting the moisture dynamics: A comprehensive review. Sustainability, 14(18), 11538. https://doi.org/10.3390/su141811538

Sripathy, K. V., & Groot, S. P. (2023). Seed development and maturation. In Seed science and technology: Biology, production, quality (pp. 17-38). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-19-5888-5_2

Suganthakrishna, S., Nirmala, R. G., Shreeram, S., & Sidharth, S. B. (2025, October). Development of a Low-Cost Capacitive Soil Moisture Monitoring System. In 2025 2nd International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF) (pp. 1-9). IEEE. https://doi.org/10.1109/ICECONF65644.2025.11379567

Taheri, M., Bigdeli, M., Imanian, H., & Mohammadian, A. (2025). An overview of machine-learning methods for soil moisture estimation. Water, 17(11), 1638. https://doi.org/10.3390/w17111638

Thakur, T., & Garg, A. (2024). Growth and flowering of ornamental pot plants influenced by growing media–A review. Journal of Ornamental Horticulture, 27(2), 95-106. https://doi.org/10.5958/2249-880X.2024.00013.6

Thenveettil, N., Bheemanahalli, R., Reddy, K. N., Gao, W., & Reddy, K. R. (2024). Temperature and elevated CO2 alter soybean seed yield and quality, exhibiting transgenerational effects on seedling emergence and vigor. Frontiers in plant science, 15, 1427086. https://doi.org/10.3389/fpls.2024.1427086

Wu, Y., Chen, R., Wang, F., Liu, X., & Chi, H. (2025). Enhanced Seedling Growth Effect of Cocopeat by Supplementation with Earthworm Manure as Nutrient Amendment. Polish Journal of Environmental Studies, 34(4), 3853. https://doi.org/10.15244/pjoes/189294

Yusuf, A. G., Al-Yahya, F. A., Saleh, A. A., & Abdel-Ghany, A. M. (2025). Optimizing greenhouse microclimate for plant pathology: challenges and cooling solutions for pathogen control in arid regions. Frontiers in Plant Science, 16, 1492760. https://doi.org/10.3389/fpls.2025.1492760

Zampieri, E., Pesenti, M., Nocito, F. F., Sacchi, G. A., & Valè, G. (2023). Rice responses to water limiting conditions: improving stress management by exploiting genetics and physiological processes. Agriculture, 13(2), 464. https://doi.org/10.3390/agriculture13020464

Published
2026-09-24
How to Cite
Fauzan, A., & Rahmadewi, R. (2026). Design and Implementation of a Multi-Zone Automatic Irrigation Control System Based on Sugeno Fuzzy Logic for a Melon Seedling Incubator . Journal La Multiapp, 7(4), 874-890. https://doi.org/10.37899/journallamultiapp.v7i4.5234