Intelligent Valve Control Mechanism for Irrigation in Precision Agriculture

Abstract

Precision agriculture, powered by IoT and machine learning, offers a promising solution to optimize water usage and enhance crop yields. This research presents an innovative Intelligent Irrigation System (IIS) that leverages real-time sensor data, predictive analytics, and mobile app interaction to achieve efficient and sustainable water management. Unlike traditional systems, our IIS employs a Raspberry Pi to collect critical data, including soil moisture, temperature, humidity, and rainfall. Advanced machine learning algorithms, such as Random Forest, analyze this data to accurately predict irrigation needs. The system's predictive capabilities enable precise valve control, delivering water to plants based on their specific requirements.By integrating IoT and machine learning, our IIS surpasses the limitations of existing solutions. It empowers farmers to make informed decisions, reduce water waste, and improve crop productivity. The system's user-friendly mobile app interface facilitates remote monitoring and control, enhancing accessibility and convenience. Our research aligns with the findings of previous studies (Abuzanouneh et al., 2022),(S, n.d.) (Water and Agriculture in India, n.d.)which demonstrate the potential of IoT-based irrigation systems in optimizing water usage. However, our IIS distinguishes itself by incorporating a comprehensive approach that combines sensor data, predictive analytics, and mobile app interaction. By adopting this intelligent irrigation solution, farmers can contribute to sustainable agriculture and address the challenges posed by climate change and water scarcity.