IoT-Based Smart Agriculture: Enhancing Crop Management and Yield Prediction
Abstract
The application of IoT in agriculture, known as smart agriculture, has the potential to significantly improve crop management and yield prediction. This paper investigates the implementation of an IoT-based smart agriculture system that monitors soil moisture, temperature, humidity, and crop health through a network of sensors. Data collected from the sensors is analyzed using machine learning algorithms to provide farmers with actionable insights and predictive analytics. Field trials conducted over multiple growing seasons demonstrate the system's effectiveness in optimizing irrigation, reducing resource wastage, and increasing crop yields. The paper also discusses the challenges and future directions for IoT in agriculture, including scalability, cost, and data privacy concerns.
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