Enhancing Smart Agriculture Through IoT-Based Crop Monitoring and Disease Detection

Abstract

The rise of the Internet of Things (IoT) has marked a significant shift in smart agriculture, providing innovative approaches to improve crop yields, optimize resource usage, and reduce risks such as crop diseases. This paper examines the use of IoT in monitoring crop fields and detecting diseases, focusing on its importance, core principles, and potential advantages. By integrating IoT sensors, data analysis, and machine learning techniques, farmers can access real-time information about environmental conditions and crop health, allowing them to implement proactive management strategies to enhance productivity and sustainability. The IoT setup, which includes NodeMCU, cameras, soil moisture sensors, and temperature sensors, facilitates monitoring of plant leaf conditions, irrigation control, and disease detection. A data-driven platform will analyze historical data and weather forecasts to offer suggestions and predictive insights. With a user-friendly interface, farmers can easily receive alerts for diseases, view real-time data, and access predictive recommendations. The platform will connect with existing farm management systems to ensure seamless data integration and support decision-making. The system's effectiveness and accuracy will be assessed, considering its impact on farmer satisfaction, pesticide usage, and crop yield. Leveraging IoT technology, smart agriculture aims to transform traditional farming methods, promoting resilience, efficiency, and innovation in the agricultural industry.