Analisis Efisiensi Energi pada Bangunan Hijau dengan Teknologi Terbaru

Abstract

The implementation of smart HVAC systems integrated with IoT sensors has emerged as a transformative approach to enhancing energy efficiency in green buildings. This study evaluates the impact of real-time environmental monitoring and adaptive energy management using IoT-based smart HVAC systems. Experimental results demonstrate a significant reduction in energy consumption, averaging 27.3%, while maintaining optimal indoor temperature and humidity stability. The predictive model, leveraging reinforcement learning, achieves an accuracy rate with an error margin of less than 1.2%, ensuring precise energy optimization. Compared to conventional energy management systems, the proposed approach offers a more responsive and adaptive solution to real-time environmental variations. Despite its potential, challenges such as high initial investment costs and industry reluctance toward adopting new technologies persist. This study underscores the necessity of policy incentives and regulatory frameworks to accelerate the adoption of smart energy solutions in green buildings. Future research should explore long-term performance across different climatic conditions and integrate renewable energy sources to further enhance sustainability.