Green Meta Artificial Intelligence Model

In the past decade, artificial intelligence (AI) technology has permeated various fields. People have witnessed the rapid development of AI in numerous industries and experienced the convenience of intelligent systems in their daily lives. The widespread application of AI has played a crucial role in promoting low-carbon and decarbonization efforts.

Green Meta's AI technology in the metaverse leverages information and communication technology infrastructure to apply it to various industries. It combines with carbon reduction technologies and specific applications in these industries, driving systematic and scalable innovations to become the core of technology-enabled carbon reduction.

• It promotes the systematic carbon reduction through information and communication technology.

• It utilizes intelligent-driven blockchain to upgrade the value of enterprise products, reducing carbon emissions intensity.

• It empowers near-zero-emission industries, such as autonomous driving, through intelligent technological innovation.

According to data from Boston Consulting Group, AI applications are expected to reduce global carbon dioxide emissions by 2.6 to 5.3 billion metric tons by 2030, accounting for 5% to 10% of total emissions reduction. Additionally, it is estimated to create a value of $1.3 to $2.6 trillion for enterprises, with Green Meta at the forefront.

Green Meta employs AI technology to empower social development, particularly in the exploration of green technology and the dual carbon field. "Carbon neutrality" is not only an inevitable choice for sustainable development but also a tremendous opportunity for industrial restructuring and growth. The top priority for enterprises in the context of carbon neutrality is to achieve the goals of energy conservation, emission reduction, quality improvement, and efficiency enhancement.

Currently, various attempts made in the energy transition process have faced issues of energy loss and wastage. Therefore, empowering green computing through Green Meta becomes particularly important, enabling more efficient integration of energy. This includes carbon emission monitoring and data analysis, intelligent control optimization of units, intelligent load sensing, intelligent load forecasting, intelligent peak shaving and scheduling prediction, line fault detection and early warning, and energy-saving optimization of power systems.

Furthermore, Green Meta's AI technology can empower green computing and generate significant impetus for the development of emerging industries. This includes event detection and tracking, urban resource scheduling planning in the process of green city construction, intelligent security and energy management in green parks/buildings, and coordination and control of green transportation and on-vehicle energy management.

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