An AI-Driven Cloud-Integrated Framework for Intelligent Crop Recommendation and Farm Resource Optimization

Abstract Agriculture is increasingly challenged by climate variability, soil degradation, pest infestations, and inefficient resource utilization. To address these issues, this paper presents Agro Smart AI, an intelligent farming advisory web application that integrates Artificial Intelligence (AI) with Cloud Computing to support data-driven agricultural decision-making. The proposed system utilizes machine learning algorithms to analyze soil characteristics, crop type, weather conditions, and historical agricultural data in order to generate accurate recommendations for crop selection, irrigation planning, fertilizer application, and disease risk assessment. Cloud infrastructure enables scalable data processing, real-time weather integration, and secure storage of agricultural data. By providing timely and personalized advisory services through a user-friendly web interface, Agro Smart AI aims to improve crop productivity, optimize resource usage, and promote sustainable farming practices. Experimental evaluation indicates that AI-driven recommendations can significantly reduce farming risks and enhance yield outcomes, making the system suitable for modern precision agriculture. Keywords: Intelligent Farming, AI-based Advisory System, Cloud-based Agriculture, Machine Learning Models, Crop Yield Optimization, Decision Support System