Smart Agriculture: IoT-Driven Soil Moisture Monitoring System for Enhanced Crop Management

Agriculture serves as the backbone of the Indian economy, ensuring food security and supporting millions of livelihoods, while significantly contributing to the nation's GDP. However, the sector faces pressing challenges, including inefficient resource utilization, unpredictable climatic conditions, and re-liance on outdated practices, which hinder productivity and sus-tainability. Addressing these issues, this paper identifies the gap in accessible, reliable, and advanced tools for soil management and presents an innovative IoT-based solution integrating Arduino sensors and neural networks. The proposed system captures real-time data on soil parameters such as moisture, temperature, and pH levels, and employs neural networks for advanced preprocessing to mitigate inaccuracies caused by sensor malfunctions or microclimatic variations. A dedicated rainfall prediction model further complements the framework by incorporating weather integration for comprehensive insights. Through rigorous testing, the system demonstrated high accuracy and reliability, enabling optimized irrigation scheduling, improved crop selection, and efficient fertilizer application, ultimately enhancing crop yields and reducing resource wastage. Farmers using the system re-ported significant improvements in decision-making confidence and operational efficiency. This integrated approach not only addresses the immediate needs of rural and small-scale farmers but also advances the goals of precision agriculture, fostering sustainable practices and contributing to the resilience of In-dian agriculture amidst growing environmental and economic pressures. By bridging the gap between traditional methods and modern technological interventions, this work lays a foundation for scalable solutions that promote food security, economic growth, and environmental conservation.