THE DEVELOPMENT AND THE IMPLEMENTATION OF AN ARDUINO-BASED AUTOMATED IRRIGATION SYSTEM FOR HYDROAGRICULTURAL EFFICIENCY

Aurel Mihail ȚÎȚU, Daniel BÂLC, Emanuel BÂLC

Abstract


This study explores an Arduino-based automated irrigation system aimed at improving hydroagricultural efficiency through precision and adaptability. Using sensors to monitor soil moisture, temperature, and other environmental factors, the system enables real-time, plant-specific irrigation decisions. Arduino microcontrollers process sensor data to dynamically control irrigation frequency and duration, optimizing water usage and enhancing plant health. Tested in a cultivation scenario, the system demonstrates potential for sustainable agriculture by reducing water waste and improving crop management. This research contributes to precision agriculture, illustrating how technology integration can support efficient resource use and better crop management practices. 

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Parikh, A. (1982). An econometric model of the agricultural sector of the Indian economy. In Journal of Policy Modeling (Vol. 4, Issue 3, pp. 395–411). Elsevier BV. https://doi.org/10.1016/0161 8938(82)90027-8

Misaghi, F., Delgosha, F., Razzaghmanesh, M., & Myers, B. (2017). Introducing a water quality index for assessing water for irrigation purposes: A case study of the Ghezel Ozan River. In Science of The Total Environment (Vol. 589, pp. 107–116). https://doi.org/10.1016/j.scitotenv.2017.02.226

Anagnostopoulos, K. P., & Petalas, C. (2011). A fuzzy multicriteria benefit–cost approach for irrigation projects evaluation. In Agricultural Water Management (Vol. 98, Issue 9, pp. 1409–1416). Elsevier BV. https://doi.org/10.1016/j.agwat.2011.04.009

Fischer, S., Pluntke, T., Pavlik, D., & Bernhofer, C. (2014). Hydrologic effects of climate change in a sub-basin of the Western Bug River, Western Ukraine. In Environmental Earth Sciences (Vol. 72, Issue 12, pp. 4727–4744). Springer Science and Business Media LLC. https://doi.org/10.1007/s12665-014-3256-z

Dalin, C., & Outhwaite, C. L. (2019). Impacts of Global Food Systems on Biodiversity and Water: The Vision of Two Reports and Future Aims. In One Earth (Vol. 1, Issue 3, pp. 298–302). Elsevier BV. https://doi.org/10.1016/j.oneear.2019.10.016

Gordon, L. J., Finlayson, C. M., & Falkenmark, M. (2010). Managing water in agriculture for food production and other ecosystem services. In Agricultural Water Management (Vol. 97, Issue 4, pp. 512–519). Elsevier BV. https://doi.org/10.1016/j.agwat.2009.03.017

Sakawa, M., Nishizaki, I., & Uemura, Y. (2000). Interactive fuzzy programming for multi-level linear programming problems with fuzzy parameters. In Fuzzy Sets and Systems (Vol. 109, Issue 1, pp. 3–19). Elsevier BV. https://doi.org/10.1016/s0165-0114(98)00130-4

Ortiz-Partida, J. P., Kahil, T., Ermolieva, T., Ermoliev, Y., Lane, B., Sandoval-Solis, S., & Wada, Y. (2019). A Two-Stage Stochastic Optimization for Robust Operation of Multipurpose Reservoirs. In Water Resources Management (Vol. 33, Issue 11, pp. 3815–3830). Springer Science and Business Media LLC. https://doi.org/10.1007/s11269-019-02337-1

Bozkurt, Y., Yazar, A., Gençel, B., & Sezen, M. S. (2006). Optimum lateral spacing for drip-irrigated corn in the Mediterranean Region of Turkey. In Agricultural Water Management (Vol. 85, Issues 1–2, pp. 113–120). Elsevier BV. https://doi.org/10.1016/j.agwat.2006.03.019


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