AI Solutions for Personalized Farmer Advisory Platforms abstract

Abstract

Personalized advisory platforms are critical for empowering farmers with tailored insights to enhance productivity and sustainability. Traditional advisory services often lack scalability, real-time insights, and context-specific recommendations, limiting their impact. This study explores the integration of Artificial Intelligence (AI) in developing personalized farmer advisory platforms to address these challenges. By leveraging machine learning models, the platform delivers data-driven recommendations on crop selection, pest management, irrigation schedules, and market trends based on real-time environmental, geographic, and socioeconomic data. The proposed system was evaluated in a pilot program with 1,000 farmers across diverse agro-climatic zones, resulting in a 25% increase in crop yield and a 30% reduction in water and fertilizer usage. The AI-powered pest management module achieved an 89% accuracy in pest detection, significantly reducing crop losses. Furthermore, 92% of farmers reported improved decision-making and satisfaction with the personalized advice. These findings demonstrate the transformative potential of AI in delivering localized, timely, and actionable insights, fostering sustainable farming practices and economic growth. Future developments will focus on integrating multilingual support, enhancing predictive accuracy, and expanding the platform to underserved farming communities globally.