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Journal of Information and Optimization Sciences

(Since 1980)
Open Access ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

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Journal of Information and Optimization Sciences
Open Access Research Article

An Internet of Things (IoT)-based smart irrigation and crop suggestion platform for enhanced precision agriculture

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pp. 873–883Vol. 45Issue 4May 2024DOI: 10.47974/JIOS-1612XML
Published Online:
08 Jun 2024
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1612
Pages:
873–883

Abstract

The country’s agriculture sector operating autonomously within the overall economic system. India is the world’s number two producer of agricultural goods. Farmers primarily focus on crop rotation, irrigation, and fertilization. Modern technological advancements have rendered farmers completely powerless when it comes to attaining optimal agricultural yields under the present weather conditions. Maximizing agricultural output via the integration of cutting-edge technological solutions must take precedence. Agricultural productivity is enhanced with the usage of the Internet of Things (IoT) as it allows for improved prediction of crop production and other factors that contribute to high yield. Soil temperature, pH, and water level are three of the many factors that influence how crops should be spaced out for maximum harvest. To help farmers who use the Internet of Things (IoT) for precision agriculture increase their crop output, this study proposes a smart irrigation system and an agriculture cultivation recommender. By analyzing water content throughout the several phases of plant development and integrating the IoT applications into agriculture, the module optimizes the water level for future irrigation decision-making, ensuring optimal crop growth and water stability in precision agriculture. Using the suggested method to keep tabs on massive agricultural areas yields good results. This method is useful for anticipating irrigation needs using a variety of sensor metrics, which in turn assists with irrigation planning. Soil moisture, soil temperature, and humidity are the characteristics used for prediction. The experimental findings presented here provide credence to the idea of smart irrigation, which may increase agricultural yields while decreasing water use.

Keywords

Agricultural Internet of Things (IoT)PrecisionSmart IrrigationDecision-making

Subject Classifications

68xx

References

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