DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE BASED VERTICAL HYDROPONIC CULTIVATION SYSTEM
Abstract
Abstract: The advancement of smart agriculture has become a promising solution to increase food productivity and land use efficiency in urban environments. This research aims to develop an Artificial Intelligence (AI)-based vertical hydroponic farming system integrated with LED grow light technology and catfish aquaponics. The proposed system combines vertical hydroponics and aquaponics to optimize plant growth and water utilization. Internet of Things technology enables real-time environmental monitoring through an Arduino Uno microcontroller integrated with LDR, soil moisture, pH, and NPK sensors. The obtained sensor data is processed using the Mamdani Fuzzy Logic algorithm, which performs fuzzification, rule inference, aggregation, and defuzzification to generate adaptive control decisions for irrigation, nutrient circulation, and LED grow light intensity. This research uses the Research and Development (R&D) method through prototype development and performance evaluation for 30 days using spinach (Amaranthus spp.) and mustard greens (Brassica juncea) as test plants. Experimental results showed that the developed system successfully maintained stable environmental conditions, with soil moisture ranging between 69–72%, a pH value between 6.4 and 6.6, and optimal nutrient availability. Plant growth increased significantly. The integration of IoT, AI and aquaponics improves cultivation efficiency, enabling environmental control as a smart and sustainable solution for urban agriculture.
Keywords: artificial intelligence; aquaponic; hydroponic; LED grow light; vertical farming
Abstract: Kemajuan pertanian cerdas telah menjadi solusi yang menjanjikan untuk meningkatkan produktivitas pangan dan efisiensi penggunaan lahan di lingkungan perkotaan. Penelitian ini bertujuan untuk mengembangkan sistem pertanian hidroponik vertikal berbasis Kecerdasan Buatan (AI) yang terintegrasi dengan teknologi lampu tumbuh LED dan aquaponik ikan lele. Sistem yang diusulkan menggabungkan hidroponik vertikal dan aquaponik untuk mengoptimalkan pertumbuhan tanaman dan pemanfaatan air. Teknologi Internet of Things memungkinkan pemantauan lingkungan secara real-time melalui mikrokontroler arduino uno yang terintegrasi dengan sensor LDR, kelembaban tanah, pH, dan NPK. Data sensor yang diperoleh diproses menggunakan algoritma Logika Fuzzy Mamdani, yang melakukan fuzzifikasi, inferensi aturan, agregasi, dan defuzzifikasi untuk menghasilkan keputusan kontrol adaptif untuk irigasi, sirkulasi nutrisi, dan intensitas lampu tumbuh LED. Penelitian ini menggunakan metode Pengembangan (R&D) melalui pengembangan prototipe dan evaluasi kinerja selama 30 hari menggunakan bayam (Amaranthus spp.) dan sawi hijau (Brassica juncea) sebagai tanaman uji. Hasil eksperimen menunjukkan bahwa sistem yang dikembangkan berhasil mempertahankan kondisi lingkungan yang stabil, dengan kelembaban tanah berkisar antara 69–72%, nilai pH antara 6,4 dan 6,6, dan ketersediaan nutrisi yang optimal. Pertumbuhan tanaman meningkat secara signifikan. Integrasi IoT, AI dan aquaponik meningkatkan efisiensi budidaya, untuk pengendalian lingkungan sebagai solusi cerdas dan berkelanjutan untuk pertanian perkotaan.
Keywords: aquaponik; kecerdasan buatan; hidroponik; lampu tumbuh LED; pertanian vertikal
References
G. Rajaseger, “Hydroponics: Current Trends in Sustainable Crop Production,” Journal of Agriculture and Food Research, vol. 15, pp. 1–12, 2023.
T. Baraskar, V. Khatri, P. Kolhe, and M. Katyarmal, “AI-Powered Automated Hydroponic System for Smart Agriculture,” MethodsX, vol. 13, pp. 1–15, 2025.
P. A. C. Setiawan, “Smart Vertical Farming: The Role of IoT in Achieving Sustainable Agriculture,” Journal of Information Technology, vol. 8, no. 2, pp. 55–67, 2025.
R. Herrera-Arroyo et al., “Smart Hydroponic Cultivation System for Lettuce Using IoT Technology,” Smart Cities, vol. 8, no. 4, pp. 110–125, 2025.
T. D. Akpenpuun, “Advancements in Vertical Farming: A Review of Potentials and Challenges,” Korean Journal of Agricultural Science, vol. 52, no. 1, pp. 77–90, 2025.
M. S. Dennison, “The Role of Automation and Robotics in Transforming Hydroponic and Aquaponic Farming,” Discover Agriculture, vol. 3, no. 2, pp. 1–18, 2025.
S. Wright and V. Hughes, “IoT and AI for Smart Aquaponics and Hydroponics Systems,” International Journal of Smart Agriculture, vol. 6, no. 1, pp. 20–35, 2025.
F. Assimakopoulos et al., “AI and Related Technologies in the Fields of Smart Agriculture,” Information Journal, vol. 16, no. 100, pp. 1–40, 2025.
M. Dutta et al., “Internet of Things-Based Smart Precision Farming in Soilless Agriculture,” International Journal of Agricultural Engineering, vol. 11, no. 3, pp. 145–160, 2025.
X. Cao et al., “IGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control,” IEEE Access, vol. 9, pp. 113421–113438, 2021.
S. A. Mozumder and A. S. M. Sharifuzzaman, “Smart IoT-Biofloc Water Management System Using Decision Regression Tree,” International Conference on Smart Agriculture, pp. 55–62, 2021.
D. Rakocy, “Recent Advances in Aquaponic Systems: A Critical Review,” Reviews in Aquaculture, vol. 17, no. 2, pp. 1–22, 2025.
J. Resh, Hydroponic Food Production, 8th ed. Boca Raton, FL, USA: CRC Press, 2021.
S. Agustian, I., Prayoga, B. I., Santosa, H., Daratha, N., & Faurina, R. (2022). NFT Hydroponic Control Using Mamdani Fuzzy Inference System. Journal of Robotics and Control.
Escalante-Mamani, J. C., et al. (2025). Design and Validation of an IoT-Integrated Fuzzy Logic Controller for pH and Electrical Conductivity Regulation in NFT Hydroponic Systems. Electronics (MDPI).
S. Kurniawan and A. Pratama, “Implementation of Arduino-Based Smart Farming Systems Using Environmental Sensors,” Journal of Agricultural Informatics, vol. 9, no. 1, pp. 66–75, 2024.
R. Pratama and A. Wijaya, “Efficiency Analysis of LED Grow Light on Hydroponic Vegetable Growth,” Journal of Smart Farming Technology, vol. 5, no. 3, pp. 88–97, 2023.
