Samsung electronics co., ltd. (20240121622). SYSTEM AND METHOD FOR AERIAL-ASSISTED FEDERATED LEARNING simplified abstract

SYSTEM AND METHOD FOR AERIAL-ASSISTED FEDERATED LEARNING

Organization Name

samsung electronics co., ltd.

Inventor(s)

Tushar Vrind of Bangalore (IN)

Debabrata Das of Bangalore (IN)

SYSTEM AND METHOD FOR AERIAL-ASSISTED FEDERATED LEARNING - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240121622 titled 'SYSTEM AND METHOD FOR AERIAL-ASSISTED FEDERATED LEARNING

Simplified Explanation

The present disclosure describes a system and method for aerial-assisted federated learning at a federated learning server. The method involves receiving parameter sets and trajectory information from user equipment and an aerial cell, selecting at least one user equipment based on the received information, and activating an aerial link between the aerial cell and the selected user equipment to include them in a set of federated user equipment associated with the federated learning server.

• Explanation of the patent/innovation:

 * System and method for aerial-assisted federated learning
 * Utilizes trajectory information and parameter sets to select user equipment
 * Activates an aerial link between an aerial cell and selected user equipment
 * Includes selected user equipment in a set of federated user equipment

Potential Applications

This technology could be applied in various fields such as:

• Telecommunications
• Internet of Things (IoT)
• Autonomous vehicles
• Surveillance systems

Problems Solved

• Enhances federated learning efficiency
• Improves data collection from user equipment
• Enables communication with user equipment in remote areas

Benefits

• Increased accuracy in machine learning models
• Enhanced privacy and security of user data
• Improved performance of federated learning systems

Potential Commercial Applications

Optimizing this technology for commercial use could lead to applications in:

• Mobile network operators
• Smart city infrastructure
• Industrial automation
• Healthcare systems

Possible Prior Art

One potential prior art for this technology could be the use of drones for data collection in various industries, but the specific application of aerial-assisted federated learning may be a novel concept.

How does this technology handle data privacy concerns?

The abstract does not provide details on how user data privacy is maintained during the aerial-assisted federated learning process. It would be important to understand the mechanisms in place to protect sensitive information.

What are the limitations of using aerial cells for communication with user equipment?

The abstract does not mention any potential limitations or challenges associated with using aerial cells for communication. It would be valuable to explore factors such as signal interference, range limitations, and cost implications.

Original Abstract Submitted

the present disclosure provides a system and a method for aerial-assisted federated learning at a federated learning (fl) server. the method includes receiving a plurality of parameter sets and trajectory information indicating a coverage range by the fl server from a plurality of user equipment (ues) and an aerial cell, respectively. further, the fl server selects at least one ue from the plurality of ues based on the received plurality of parameter sets and the received trajectory information. additionally, the fl server triggers an activation of the aerial link between the aerial cell and the selected at least one ue to include the selected at least one ue to a set of federated ues associated with the fl server.