IoT for Agricultural Innovation: Enhancing Robusta Coffee Seedling Growth in Controlled Environments with Intelligent Air Quality Control System (IAQCS)
DOI:
https://doi.org/10.25047/tefa.v2i1.5752Keywords:
Coffee Robusta, IoT, IAQCS, NurseryAbstract
Advancements in Internet of Things (IoT) technology have revolutionized agriculture by enabling real-time monitoring and automated environmental control to optimize crop growth. This study focuses on evaluating the impact of IoT implementation on greenhouse environmental stability and the growth of Robusta Coffee Clone BP 308 seedlings, emphasizing plant height and leaf count as key parameters. The IoT system incorporates DHT11/DHT22 sensors for temperature and humidity monitoring, soil pH sensors, and an ESP8266 WiFi module for data transmission to an IoT platform. Additionally, Fuzzy Logic algorithms were employed to analyze the data and regulate environmental conditions such as temperature and humidity automatically. The experimental design compared IoT-based systems with conventional methods in a controlled greenhouse environment. Results demonstrated that the IoT system significantly enhanced environmental stability, maintaining an average temperature of 26.59°C and humidity of 86.46%, compared to conventional systems with greater fluctuations of 28.43°C and 82.69%. This stability positively impacted seedling growth, with IoT-treated plants achieving significantly higher heights and leaf counts at weeks 3, 6, and 9. By week 9, IoT-treated seedlings averaged a height of 24.00 cm with 11.73 leaves, outperforming non-IoT seedlings, which reached only 14.07 cm with 8.27 leaves. These findings highlight IoT's potential to create optimal growth conditions, reduce environmental stress, and enhance photosynthetic efficiency. Furthermore, IoT's precision in managing resources supports sustainable agriculture, making it an essential tool for improving productivity and competitiveness, especially in coffee cultivation, a key commodity in Indonesia.
References
[1] M. N. O. Sadiku et al., “Internet of Things in Agriculture : A Primer,” vol. 2, no. 2, pp. 215–220, 2021, doi: 10.51542/ijscia.v2i2.24.
[2] C. Lee, R. Strong, G. Briers, T. Murphrey, N. Rajan, and S. Rampold, “A Correlational Study of Two U . S . State Extension Professionals ’ Behavioral Intentions to Improve Sustainable Food Chains through Precision Farming Practices,” 2023.
[3] F. Y. Ali, E. Rosdiana, H. F. Rohman, and R. N. Kusumaningtyas, “Increasing the Growth of Robusta Coffee Seedlings ( Coffea anephora ) Through Application of KNO 3 and Shallot Extract,” vol. 6, no. 02, pp. 585–594, 2024.
[4] A. F. Amalia, H. S. P. Rahayu, Y. P. Rahardjo, L. Hutahaean, and E. S. Rohaeni, “Revista Brasileira de Engenharia Agrícola e Ambiental Artificial intelligence for small hydroponics farms employing fuzzy logic systems and economic analysis 1 Inteligência Artificial para pequenas fazendas hidropônicas empregando sistemas de lógica fuzzy e análise econômica,” pp. 690–697, 2023.
[5] A. Regina et al., “Fuzzy logic in automation for interpretation of adaptability and stability in plant breeding studies,” no. April, pp. 123–129, 2019.
[6] A. Mentsiev, “Strategic integration of technology in precision agriculture,” vol. 01026, 2024.
[7] A. A. R. Madushanki, M. N. Halgamuge, W. A. H. S. Wirasagoda, and A. Syed, “Adoption of the Internet of Things ( IoT ) in Agriculture and Smart Farming towards Urban Greening : A Review,” vol. 10, no. 4, pp. 11–28, 2019.
[8] M. S. Farooq, S. Riaz, A. Abid, K. Abid, and M. A. Naeem, “A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming,” IEEE Access, vol. 7, pp. 156237–156271, 2019, doi: 10.1109/ACCESS.2019.2949703.
[9] M. S. Farooq, S. Riaz, A. Abid, T. Umer, and Y. Bin Zikria, “Role of IoT Technology in Agriculture : A Systematic Literature Review,” 2020.
[10] R. C. Santos, “Smart sensors and Internet of Things ( IoT ) for sustainable environmental and agricultural management Sensores inteligentes e Internet das Coisas ( IoT ) para gestão ambiental e agrícola sustentável,” pp. 2692–2714, 2023, doi: 10.54033/cadpedv20n7-014.
[11] A. Rohman, S. Maesaroh, A. Mustopa, and R. M. Febrian, “The Implementation of The Internet of Things in The Duck Egg Incubator Monitoring System,” vol. 3, no. 2, pp. 84–90, 2022, doi: 10.38043/tiers.v3i2.3891.
[12] M. Sagheer, A., Mohammed, M., Riad, K., & Alhajhoj, “A Cloud-Based IoT Platform for Precision Control of Soilless Greenhouse Cultivation,” pp. 1–28, 2020.
[13] S. Gao, “The Application of Information Classification in Agricultural Production Based on Internet of Things and Deep Learning,” IEEE Access, vol. 10, pp. 22622–22630, 2022, doi: 10.1109/ACCESS.2022.3154607.
[14] C. Bhoyar, K. P. Kanojia, and B. Chourasia, “Design of an efficient IoT based irrigation platform via fuzzy bioinspired multisensory analysis of on-field parameter sets,” vol. 14, pp. 107–123, 2023, doi: 10.22545/2023/00225.
[15] J. Kumar et al., “Development and evaluation of automation system for irrigation scheduling in broccoli ( Brassica oleracea ),” vol. 91, no. May, pp. 796–798, 2021.
[16] A. Kalandarov, P., Kutlimurotov, Z., Eshchanova, G., & Mustafakulov, “Automated control system of drip irrigation and mathematical modeling Automated control system of drip irrigation and mathematical modeling,” 2023, doi: 10.1088/1755-1315/1142/1/012052.
[17] P. M. N. Rani, A. P. S. Thengal, P. Hangsing, L. I. P. Ray, T. Rajesh, and K. Datta, “A Simulation Model for the Smart Irrigation System using Arduino,” vol. 8, no. 2, pp. 7–14, 2019, doi: 10.17148/IJARCCE.2019.8202.
[18] E. Rosdiana, J. E. Rahma, F. Y. Ali, U. Setyoko, and D. C. Anindita, “Test of Level of Likes on Fermentation Length and Physical Quality Characteristics of Robusta Coffee After Storage,” vol. 5, no. 2, pp. 88–93, 2024, doi: 10.25077/jrp.5.2.88-93.2024.
[19] S. Gali et al., “International Journal of Research Publication and Reviews Design and Implementation of Automatic Agricultural Robot – Agrobot,” vol. 4, no. 4, pp. 3473–3477, 2023.
[20] B. Memić, A. H. Džubur, and E. Avdagić-golub, “Green IoT : Sustainability Environment and Technologies,” vol. 2, no. 1, pp. 24–29, 2022.
[21] I. Griha, T. Isa, and A. Effendi, “Deep reinforcement learning in agricultural IoT- based : A review,” vol. 07004, pp. 0–5, 2024.
[22] D. M. Quan and T. T. H. Van, “Potential and Trends of IoT Application in Agriculture in Vietnam,” vol. 04, no. 03, pp. 666–676, 2023.
[23] H. Ping, J. Wang, Z. Ma, and Y. Du, “Mini-review of application of IoT technology in monitoring agricultural products quality and safety,” vol. 11, no. 5, pp. 35–45, 2018, doi: 10.25165/j.ijabe.20181105.3092.
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Copyright (c) 2024 Eva Rosdiana, Fandyka Yufriza Ali, Estin Roso Pristiwaningsih, Rani Purbaningtyas, Didit Rahmat Hartadi, Denny Trias Utomo
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