AI-Driven Digital Twins for Climate-Resilient Precision Agriculture

This research presents an AI-driven Digital Twin framework for climate-resilient precision agriculture. The proposed system integrates Internet of Things (IoT), Artificial Intelligence (AI), and real-time data analytics to monitor crop conditions, simulate environmental scenarios, and optimize resource utilization. The digital twin model enables predictive analysis for irrigation, crop health, and climate adaptation strategies. The system improves agricultural productivity, reduces resource wastage, and supports sustainable farming. The results demonstrate enhanced decision-making and resilience against climate variability.