AI-Driven Automation for Green Buildings and Sustainable Agriculture: Enhancing Efficiency, Scalability, and Resource Management

The integration of artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) is transforming green buildings and sustainable agriculture by enhancing energy efficiency, predictive maintenance, and resource optimization. This study presents an AIdriven framework incorporating Ensemble Learning, Transfer Learning, and Federated Learning to improve decision-making while ensuring privacy and scalability. Edge AI and IoT enable real-time automation, reducing cloud dependency and operational costs. AI-powered HVAC systems optimize energy use in smart buildings, while AI-IoT synergy improves plant disease detection and precision farming. Explainable AI techniques like LIME and SHAP enhance transparency, making AI-driven insights more interpretable for stakeholders. With a 94% accuracy improvement over traditional methods, this approach minimizes energy wastage, enhances decisionmaking, and supports sustainable, cost-effective smart environments. The study demonstrates the potential of AI to drive eco-friendly advancements in smart buildings and precision agriculture.