Enhancing Energy Efficiency in Green Buildings through Artificial Intelligence

Artificial Intelligence (AI) is poised to revolutionize the architectural design and energy management of green buildings, offering significant advancements in sustainability and efficiency. This paper explores the transformative impact of AI on improving energy efficiency and reducing carbon emissions in commercial buildings. By leveraging AI algorithms, architects can optimize building performance through advanced environmental analysis, automation of repetitive tasks, and real-time data-driven decision-making. AI facilitates precise energy consumption forecasting and integration of renewable energy sources, enhancing the overall sustainability of buildings. Our study demonstrates that AI can reduce energy consumption and CO2 emissions by approximately 8% and 19%, respectively, in typical mid-size office buildings by 2050 compared to conventional methods. Further, the combination of AI with energy efficiency policies and low-emission energy production is projected to yield reductions of up to 40% in energy consumption and 90% in CO2 emissions. This paper provides a systematic approach for quantifying AI's benefits across various building types and climate zones, offering valuable insights for decision-makers in the construction industry.

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Publication Details

Journal
Frontiers in Science and Engineering
Published
2024-08-21
DOI
https://doi.org/10.54691/py2h2y60
Citations
11
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
2.26
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article

Enhancing Energy Efficiency in Green Buildings through Artificial Intelligence

Feng Zhang, Qian Meng, Minyue Ge
11 citations
Frontiers in Science and Engineering
Air Quality Monitoring and Forecasting
2.26
article

Enhancing Energy Efficiency in Green Buildings through Artificial Intelligence

Feng Zhang, Qian Meng, Minyue Ge
article en
11 citations

Abstract

Artificial Intelligence (AI) is poised to revolutionize the architectural design and energy management of green buildings, offering significant advancements in sustainability and efficiency. This paper explores the transformative impact of AI on improving energy efficiency and reducing carbon emissions in commercial buildings. By leveraging AI algorithms, architects can optimize building performance through advanced environmental analysis, automation of repetitive tasks, and real-time data-driven decision-making. AI facilitates precise energy consumption forecasting and integration of renewable energy sources, enhancing the overall sustainability of buildings. Our study demonstrates that AI can reduce energy consumption and CO2 emissions by approximately 8% and 19%, respectively, in typical mid-size office buildings by 2050 compared to conventional methods. Further, the combination of AI with energy efficiency policies and low-emission energy production is projected to yield reductions of up to 40% in energy consumption and 90% in CO2 emissions. This paper provides a systematic approach for quantifying AI's benefits across various building types and climate zones, offering valuable insights for decision-makers in the construction industry.

Frontiers in Science and EngineeringVol. 4(8)
University of Technology Sydney (AU), University of Southern California (US), Southeast University (CN)
Affordable and clean energy
Openalex Percentile: Top 13%
Air Quality Monitoring and Forecasting
2.26
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Enhancing Energy Efficiency in Green Buildings through Artificial Intelligence — Feng Zhang, Qian Meng, et al. · Frontiers in Science and Engineering (2024) | TGRS Research Map | TGRS