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Enhancing Environmental Sustainability in Green Building Energy Consumption

This report published by Scientific Reports investigates how an active-learning based machine learning approach can can enhance environmental sustainability.

According to Scientific Reports, green building (GB) techniques are essential for reducing energy waste in the construction sector, which accounts for almost 40% of global energy consumption. Despite their importance, challenges such as occupant behavior and energy management gaps often result in GBs consuming up to 2.5 times more energy than intended. To address this, Building Automation Systems (BAS) play a crucial role in enhancing energy efficiency. This research develops a predictive model for GB design using machine learning to minimize energy consumption and improve indoor sustainability. The dataset is utilized to predict cooling and heating individually, with data visualization by graphically illustrating dataset features and preprocessing through Z-Score normalization and dataset splitting. The proposed model, based on active learning and utilizing ML regressors such as Random Forest (RF), Decision Tree (DT), Gradient Boosting (GB), Extreme Gradient Boosting (XGBoost), CatBoost (CB), Light Gradient Boosting Machine (LGBM), K-Nearest Neighbor (KNN), and Logistic Regressor (LR), shows significant performance improvements. The CBR-AL model achieves impressive results with values of 0.9975 for cooling (Y1) and 0.9883 for heating (Y2), indicating a high level of accuracy. The model’s success in reducing energy consumption and improving sustainability has potential ripple effects, including substantial cost savings, reduced carbon footprints, and improved operational efficiency in green buildings. This approach not only enhances environmental sustainability but also sets a benchmark for future advancements in predictive modelling for energy management.

Introduction

The global pursuit of sustainability greatly depends on the built environment. Green buildings are a leading indicator of achievement in this attempt because of their low environmental impact and effective use of resources. To advance the sustainability agenda and guarantee an economically viable and sustainable future for communities globally, it is imperative to integrate cutting-edge technologies with the principles of green building1. The concept of sustainable development in the built environment is the idea of designing environment that includes human activity with the limited use of the resources, limited environmental degradation and more sustainable communities. Since the built environment is mostly responsible for the world’s energy consumption and carbon emissions, transforming it into a sustainable state is essential to reducing global warming and preserving ecological integrity for future generations2. Environmental sustainability aims for building less vulnerable communities, by designing for passive heating and cooling and installing green infrastructure, which can promote economic development and job creation without harming the environment3.

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