Smart Farming - Precision Agriculture Using ML

Abstract

Agriculture is the backbone of global food production, and with the rising population, the demand for sustainable farming solutions is more critical than ever. The Smart Farming Precision Agriculture project leverages Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), and drones to tackle major agricultural challenges and optimize farming operations. This system integrates IoT sensors to enable real-time data collection on crucial factors such as soil health, weather conditions, temperature, and crop status. By analyzing this data, machine learning models provide accurate predictions on crop growth, disease risks, and yield estimation. Automated features like smart irrigation, pest detection, and nutrient monitoring help farmers make informed decisions, reducing resource wastage and improving efficiency. A key feature of the project is drone-based monitoring and spraying, which ensures precise pesticide and fertilizer application, minimizing environmental impact while maximizing productivity. Additionally, CCTV surveillance enables 24/7 field monitoring, enhancing security and protecting crops from external threats like wild animals or theft. The system also includes mobile app integration, allowing farmers to receive real-time alerts, crop recommendations, and remote irrigation control, making farm management more accessible and user-friendly. The proposed solution is cost-effective, eco-friendly, and focused on long-term sustainability and profitability. By incorporating AI-driven automation, it not only improves yield but also ensures better crop protection with minimal human intervention. This project empowers farmers with data-driven insights, enabling precision farming techniques that lead to higher productivity, reduced costs, and enhanced food security.