Year: 2025
Type: article
Abstract: This project leverages generative AI to revolutionize agricultural practices by integrating advanced data analysis, predictive modeling, and real-time monitoring systems. By analyzing soil characteristics such as pH, moisture content, nutrient levels, and texture, the AI system provides farmers with precise crop recommendations tailored to specific soil conditions, ensuring optimal growth and yield. The system also considers environmental factors like temperature, humidity, and sunlight exposure to further refine crop suggestions. This enables farmers to plan their activities, such as planting, irrigation, and harvesting, more effectively, mitigating the impact of adverse weather conditions. Additionally, the system employs image analysis to detect potential crop diseases early by comparing images of crops with a comprehensive database of known diseases. This early diagnosis facilitates timely interventions, reducing crop losses and ensuring healthy produce. By offering accurate recommendations and predictions, the system helps farmers achieve higher yields and better-quality produce, ensuring a stable food supply and addressing issues of food security. The promotion of sustainable agricultural practices reduces the environmental impact of farming and ensures the long-term viability of agricultural activities. Additionally, the improved productivity and reduced losses lead to higher profits for farmers, contributing to economic growth in the agricultural sector.
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4410133511