Internet-of-Things (IoT)-Based Smart Agriculture and Precision Irrigation for Agriculture- an Intelligent Water Management
Abstract
The agricultural industry is experiencing a transformative shift through the adoption of Internet-of-Things (IoT) technology, often termed as "smart agriculture." This paradigm shift is revolutionizing traditional farming practices, making them more precise, efficient, and data-driven. This study presents a novel contribution to the field by developing an intelligent water management system using IoT sensors, specifically designed for precision irrigation. Unlike existing systems, this solution enables real-time monitoring of critical environmental parameters such as soil moisture, humidity, and temperature with unparalleled accuracy. The unique contribution of this work lies in its data-driven approach to optimizing irrigation practices, which not only enhances water-use efficiency but also significantly improves crop yield and quality. Furthermore, the system's capability for remote monitoring and management minimizes the need for manual interventions, thereby reducing operational costs. The study demonstrates the practical application of IoT in mitigating water management issues and increasing agricultural productivity, particularly in the context of climate change challenges. This work provides a scalable and sustainable model for IoT adoption in agriculture, offering a robust framework for improving efficiency, sustainability, and resilience in farming practices.
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K. Taneja and S. Bhatia, "Automatic irrigation system using Arduino UNO," in Proc. Int. Conf. Intell. Comput. Control Syst. (ICICCS), vol. 2018, pp. 132–135, 2018.
B. Sharma et al., "Water use efficiency in agriculture: measurement, current situation and trends," in Managing Water and Fertilizer for Sustainable Agricultural Intensification, Int. Fertilizer Ind. Assoc., Paris, pp. 39–64, 2015.
L. Pipia, F. Pérez, A. Tardà, L. Martínez, and R. Arbiol, "Simultaneous usage of optic and thermal hyper spectral sensors for crop water stress characterization," in Proc. IEEE Int. Geosci. Remote Sens. Symp., 2012.
R. Blakeman, "The identification of crop disease and stress by aerial photography," Agric. Food Sci. Environ. Sci., 1990, doi: 10.1016/B978-0-408-04767-8.50020-7.
K. Balakrishna, T. Aishwarya, H. Anjitha, D. Chaithra, and Venkataramana, "An intelligent water management in farming through the IoT," Int. J. Res. Electron. Comput. Eng., vol. 7, no. 2, 2019.
L. Zhang, I. Dabipi, and W. Jr., "Internet of Things applications for agriculture," Dept. Eng. Aviat. Sci., Univ. Maryland Eastern Shore, 2018, doi: 10.1002/9781119456735.ch18.
P. Baronti et al., "Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards," Comput. Commun., vol. 30, no. 7, pp. 1655–1695, 2007, doi: 10.1016/j.comcom.2006.12.020.
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P. Lakshmi et al., "An intelligent IoT sensor coupled precision irrigation model for agriculture," Meas.: Sensors, 10.1016/j.measen.2022.100608. vol. 25, p. 100608, 2022, doi:
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C. Fathy and H. Ali, "A secure IoT-based irrigation system for precision agriculture using the expeditious cipher," Sensors, vol. 23, no. 4, p. 2091, 2023, doi: 10.3390/s23042091.
E. Karunathilake et al., "The path to smart farming: Innovations and opportunities in precision agriculture," Agriculture, vol. 13, no. 8, p. 1593, 2023, doi: 10.3390/agriculture13081593.
F. Taghvaei and R. Safa, "Efficient energy consumption in smart buildings using personalized NILM-based recommender system," Big Data Comput. Visions, vol. 2, no. 4, pp. 53–65, 2022, doi: 10.22105/bdcv.2022.325031.1039.
S. Alam, "Security concerns in smart agriculture and blockchain-based solution," in Proc. OPJU Int. Technol. Conf. Emerg. Technol. Sustain. Dev. (OTCON), Raigarh, India, pp. 16, 2023, doi: 10.1109/OTCON56053.2023.10113953.
S. Biswas and S. Podder, "Application of IoT in smart farming and precision farming: A review," in Fog Comput. Intell. Cloud IoT Syst., C. Banerjee et al., Eds., Wiley, pp. 169190, 2024, doi: 10.1002/9781394175345.ch11.
J. Pourqasem, D. Tešić, and E. Abdolmaleki, "Leveraging IoT and Industry 4.0 for enhanced environmental safety," Comput. Appl. Nanotechnol., 2023, doi: 10.22105/cand.2023.166517.
A. Abdel-Monem, A. Nabeeh, and M. Abouhawwash, "An integrated neutrosophic regional management ranking method for agricultural water management," Neutrosophic Sets Syst., 2023, doi: 10.61356/j.nswa.2023.4.
M. Saeed et al., "Unveiling efficiency: Investigating distance measures in wastewater treatment using interval-valued neutrosophic fuzzy soft set," Neutrosophic Sets Syst., 2024, doi: 10.61356/j.nswa.2024.1512356.
M. Mohamed, "Agricultural sustainability in the age of deep learning: Current trends, challenges, and future trajectories," Sustain. Manage. Innov. J., 2023, doi: 10.61185/SMIJ.2023.44102.
M. Mohamed, A. Salam, J. Ye, and R. Yong, "A hybrid triangular fuzzy SWARAMAROCS approach for selecting optimal and smart logistic enterprise based on IoT, blockchain, and UAVs," Math. Water Appl., 2024, doi: 10.61356/j.mawa.2024.4241.
V. Malavade and P. Akulwar, "Role of IoT in agriculture," IOSR J. Comput. Eng. (IOSRJCE), vol. 18, no. 2, pp. 56–57, 2016.
V. Anne, K. Durg, R. Muddineni, and S. Peri, "Smart irrigation using WSN based on IoT," Int. J. Eng. Technol., vol. 7, no. 2.8, p. 331, Mar. 2018.
Published
2025-06-30
How to Cite
KUMAR SHARMA, Vineet; JEBERSON, Wilson; KUMAR ISAAC, Rajendra.
Internet-of-Things (IoT)-Based Smart Agriculture and Precision Irrigation for Agriculture- an Intelligent Water Management.
Yugoslav Journal of Operations Research, [S.l.], june 2025.
ISSN 2334-6043.
Available at: <https://yujor.fon.bg.ac.rs/index.php/yujor/article/view/1346>. Date accessed: 07 july 2025.
doi: https://doi.org/10.2298/YJOR240315014S.
Issue
Section
Research Articles
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
