Agriculture faces increasing challenges due to climate variability, resource limitations, and the need for sustainable productivity. This paper presents an AI-Powered Smart Crop Advisory and Monitoring Platform that leverages artificial intelligence and data analytics to support informed agricultural decision-making. The system analyzes historical crop data, soil characteristics, weath-er patterns, and satellite imagery to assess crop health and growth conditions. Machine learning models generate accurate recommendations for irrigation planning, fertilizer management, pest and disease identification, and yield prediction. Image processing and computer vision techniques enable early detection of crop stress and diseases, reducing potential losses. The platform pro-vides timely, location-specific advisory services to farmers, improving crop quality and resource efficiency. By minimizing dependency on manual expertise and enhancing precision farming practices, the proposed solution contributes to increased agricultural productivity, economic sus-tainability, and food security. The system demonstrates the potential of artificial intelligence as a reliable tool for modern, data-driven agriculture.
Devi et al. (Thu,) studied this question.