تجاوز إلى المحتوى الرئيسي

Artificial intelligence for calculating and predicting building carbon emissions: a review

ملخص البحث

The construction industry, being responsible for a large share of global carbon emissions, needs to reduce its high carbon output to meet carbon reduction goals. Artificial intelligence can provide efficient support for carbon emission calculation and prediction. Here, we review the use of artificial intelligence techniques in forecasting, management and real-time monitoring of carbon emissions, focusing on how they are applied, their impacts, and challenges. Compared to traditional methods, the prediction accuracy of artificial intelligence models has increased by 20%. Artificial intelligence-driven systems could reduce carbon emissions by up to 15% through real-time monitoring and adaptive management strategies. Artificial intelligence applications improve energy efficiency in buildings by up to 25%, while reducing operational costs by up to 10%. Artificial intelligence supports the establishment of a digital carbon management system and contributes to the development of the carbon trading market.

مؤلف البحث
Jianmin Hua, Ruiyi Wang, Ying Hu, Zimeng Chen, Lin Chen, Ahmed I. Osman, Mohamed Farghali, Lepeng Huang, Ji Feng, Jun Wang, Xiang Zhang, Xingyang Zhou & Pow-Seng Yap
تاريخ البحث
مجلة البحث
Environmental Chemistry Letters
مؤلف البحث
صفحات البحث
783–816
الناشر
Springer
عدد البحث
23
موقع البحث
https://link.springer.com/article/10.1007/s10311-024-01799-z
سنة البحث
2025