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Buildings’ energy consumption and greenhouse gas emissions are a major global concern. Healthcare buildings, being crucial to society, pose particular challenges due to their round-the-clock operation and stringent hygiene standards. This paper comprehensively reviews existing literature to promote energy-efficient and comfortable healthcare buildings. The research explores both passive measures, such as orientation, materials, and daylight, and active measures, including Heating, Ventilation, and Air Conditioning systems, energy management, and renewable resources. The paper emphasizes the critical role of user behavior in conserving energy and outlines how factors like building size, operation hours, and climate can impact resource consumption. It highlights the importance of solar power as a prominent renewable energy source. It offers design and retrofitting options to enhance healthcare buildings and addresses the lack of research on small-scale healthcare buildings. The paper emphasizes maintaining a balance between user comfort and energy reduction, involving diverse stakeholders, and exploring benchmarks, automated shading, geothermal sources, local materials, and their impact on carbon emissions. This review aims to contribute to environmentally responsible and socially resilient healthcare infrastructure and provide insights for future challenges in creating energy-efficient healthcare buildings.

Data-science is a key component of modern science since it fuels AI, ML and data analytics, etc. As the electrical grid has been modernized into a smart grid, it has also become increasingly dependent on data science to monitor and control grid activity. Realistic data is essential to evaluating the algorithm’s workability but it is difficult to obtain real smart meter data due to strict privacy and security policies of many countries. In this paper, using the prophet library, we code and develop a prediction-based Synthetic Data Generator GUI, which generate the synthetic data sets.