International Journal of Frontiers in Engineering Technology, 2024, 6(5); doi: 10.25236/IJFET.2024.060512.
Gao Jiaze
School of Business Administration, Liaoning University of Science and Technology, Anshan, Liaoning, China
This article deeply explores how state-owned metallurgical enterprises use big data and artificial intelligence technology to empower innovative practices in low-carbon production processes in the context of global and Chinese "double carbon" goals[1]. By analyzing the current situation and challenges of state-owned metallurgical enterprises in carbon emission control, the article explains the application value of big data and AI technology in optimizing production processes, improving energy efficiency, and reducing emissions[2]. Through specific case presentations, it is revealed how these technologies can help state-owned metallurgical enterprises achieve green transformation and enhance their competitiveness. Finally, the article summarizes the challenges and response strategies, and looks forward to the continued application of big data and AI technology in the low-carbon transformation of the metallurgical industry in the future.
big data, artificial intelligence (AI), low-carbon production, state-owned metallurgical enterprises, dual carbon goals, green transformation, technological innovation
Gao Jiaze. Big data and AI empower innovative practices in low-carbon production processes. International Journal of Frontiers in Engineering Technology (2024), Vol. 6, Issue 5: 85-92. https://doi.org/10.25236/IJFET.2024.060512.
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