气候变化
联营
碳纤维
大气(单位)
温室气体
计算机科学
人工智能
气象学
生态学
地理
算法
生物
复合数
作者
A.K. Priya,D. Balaji,Avinash Alagumalai,Hua Song
标识
DOI:10.1016/j.scitotenv.2023.163913
摘要
Carbon capturing is imperative to fight climate change as much carbon emissions are liberated into the atmosphere, leading to adversely negative environmental impacts. Today's world addresses all the issues with the aid of digital technologies like data pooling and artificial intelligence (AI). Accordingly, this study is articulated based on AI-assisted carbon capturing. Techniques including machine learning (ML), deep learning (DL), and hybrid techniques being adopted in carbon capture are discussed. The role of AI tools, frameworks, and mathematical models are also discussed herein. Furthermore, the confluence of AI in carbon capture patent landscape is explored. This study would allow researchers to envision the growth of AI-assisted carbon capture in mitigating climate change and meeting SDG 13 - climate action.
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