Abstract: Efficient water management is a critical challenge in modern agriculture, especially under the pressures of climate change and increasing food demands. This research presents the design and implementation of a Smart Irrigation System leveraging Internet of Things (IoT) technology, real-time sensor networks, and cloud-based analytics. The system utilizes soil moisture sensors, temperature sensors, and weather forecasting data to automate irrigation schedules, significantly reducing water consumption while enhancing crop productivity.
A microcontroller-based architecture (using Arduino/ESP32) processes sensor inputs and triggers irrigation actions through wireless communication protocols. A mobile application and web dashboard provide farmers with real-time monitoring and remote -control capabilities. Field tests demonstrate that the proposed smart system can save up to 40–60% of water compared to traditional irrigation methods.
This study also highlights the scalability, cost-effectiveness, and environmental benefits of smart irrigation, paving the way for broader adoption of precision agriculture technologies. Future work will focus on integrating machine learning algorithms for predictive irrigation and expanding the system to accommodate large-scale farming operations.
Keywords: Precision Agriculture, Soil Moisture Monitoring, Sensor Networks, Climate-Adaptive Irrigation, Water Conservation
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