18347352. ARTIFICIAL INTELLIGENCE APPLICATION PROVISION METHOD AND APPARATUS FOR SUPPORTING EDGE COMPUTING FOR CYBER-PHYSICAL SYSTEMS simplified abstract (ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE)

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ARTIFICIAL INTELLIGENCE APPLICATION PROVISION METHOD AND APPARATUS FOR SUPPORTING EDGE COMPUTING FOR CYBER-PHYSICAL SYSTEMS

Organization Name

ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor(s)

Young-Joo Kim of Daejeon (KR)

ARTIFICIAL INTELLIGENCE APPLICATION PROVISION METHOD AND APPARATUS FOR SUPPORTING EDGE COMPUTING FOR CYBER-PHYSICAL SYSTEMS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18347352 titled 'ARTIFICIAL INTELLIGENCE APPLICATION PROVISION METHOD AND APPARATUS FOR SUPPORTING EDGE COMPUTING FOR CYBER-PHYSICAL SYSTEMS

Simplified Explanation

The patent application abstract describes a method and apparatus for supporting Edge computing for Cyber-Physical Systems (EdgeCPS) using artificial intelligence applications. The method involves receiving an artificial intelligence application and service specification, obtaining relevant information from an artificial intelligence information sharing database, creating a pipeline specification, and allocating resources to respective pipelines based on the specification.

  • The method involves receiving an artificial intelligence application and service specification.
  • Relevant information is obtained from an artificial intelligence information sharing database.
  • A pipeline specification is created corresponding to the artificial intelligence application and service specification.
  • Resources are allocated to respective pipelines using the pipeline specification.

Potential Applications

The technology described in the patent application could be applied in various industries such as manufacturing, healthcare, transportation, and smart cities to enhance the efficiency and performance of Edge computing systems.

Problems Solved

This technology addresses the challenges of efficiently deploying and managing artificial intelligence applications in Edge computing environments for Cyber-Physical Systems, improving overall system performance and resource utilization.

Benefits

The benefits of this technology include optimized resource allocation, improved system performance, enhanced scalability, and better support for real-time decision-making in Edge computing environments.

Potential Commercial Applications

A potential commercial application of this technology could be in the development of Edge computing solutions for smart factories, autonomous vehicles, healthcare monitoring systems, and smart infrastructure projects.

Possible Prior Art

One possible prior art for this technology could be existing methods for deploying artificial intelligence applications in cloud computing environments, which may not be optimized for Edge computing systems.

Unanswered Questions

How does this technology impact the energy efficiency of Edge computing systems?

This article does not specifically address the energy efficiency aspect of the technology. However, optimizing resource allocation and improving system performance could potentially lead to energy savings in Edge computing environments.

What are the security implications of deploying artificial intelligence applications in Edge computing for Cyber-Physical Systems?

The article does not delve into the security aspects of the technology. It would be important to consider how the deployment of AI applications in EdgeCPS could impact system security and potential vulnerabilities that need to be addressed.


Original Abstract Submitted

Disclosed herein are an artificial intelligence application provision method and apparatus for supporting Edge computing for Cyber-Physical Systems (EdgeCPS). The artificial intelligence application provision method includes receiving an artificial intelligence application and service specification, obtaining artificial intelligence-related information allocated from an artificial intelligence information sharing database based on the artificial intelligence application and service specification, creating a pipeline specification corresponding to the artificial intelligence application and service specification, and allocating resources corresponding to respective pipelines using the pipeline specification.