Terminal-Cloud Data Processing via Anonymization and Segmentation

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Solution Overview

Problem

Conventional cloud computing methods for analyzing user activities are inefficient in terms of operating expenses, performance, and privacy, as they often require static resource distribution and expose personal information, especially with the increasing data generated by IoT devices.

Innovation Solution

A terminal and cloud apparatus system that cooperatively processes personalized data, allowing adaptive resource usage and anonymization of user data, enabling flexible data distribution and protection of user privacy through tiered data processing and sharing controls.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If data is analyzed using a centralized cloud service, then service capability is provided, but personal information is excessively exposed and privacy is invaded

Engineering Contradiction:
Improveservice capabilityVSAvoidprivacy exposure
Core Design Contradiction:
ProductivityVSObject-affected harmful factors

Solution Approach 1:

The patent segments the centralized cloud analysis into distributed analysis across multiple terminals. Each terminal analyzes local data independently or collaboratively with nearby terminals, rather than sending all data to a central cloud. This segmentation maintains service capability while reducing privacy exposure by keeping sensitive data localized.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary mechanism where terminals exchange only necessary anonymized or aggregated data with nearby terminals rather than exposing raw personal information to centralized cloud servers. This intermediary approach enables service delivery while filtering out sensitive information.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Device complexity

If resources are statically distributed between terminal and cloud apparatus, then system simplicity is maintained, but resource utilization is not adaptive

Engineering Contradiction:
Improvesystem simplicityVSAvoidresource utilization adaptability
Core Design Contradiction:
Device complexityVSAdaptability or versatility

Solution Approach 1:

The patent implements dynamic resource distribution where terminals can adaptively allocate computing resources based on local conditions and service requirements. The system transitions from static cloud-terminal resource distribution to dynamic peer-to-peer resource sharing, allowing terminals to act as both consumers and providers of computing resources.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

Terminals autonomously manage their own resource allocation and can independently perform data analysis tasks without requiring centralized cloud coordination. Each terminal serves itself and neighboring terminals, enabling adaptive resource utilization while maintaining system simplicity.

Inventive Principle:
Principle #25Self-service

3Productivity

If data is offloaded only in one direction from terminal to cloud apparatus, then data processing capability is provided, but system expandability is limited when machine data is included

Engineering Contradiction:
Improvedata processing capabilityVSAvoidsystem expandability
Core Design Contradiction:
ProductivityVSAdaptability or versatility

Solution Approach 1:

The patent creates a universal data processing framework where any terminal can function as both data source and processing node. The system supports multiple data types (user data, machine data, sensor data) and multiple processing modes (local analysis, collaborative analysis, cloud analysis) without requiring different system architectures, thereby enhancing expandability.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent adds a spatial dimension to data processing by enabling horizontal peer-to-peer communication between terminals in addition to vertical terminal-cloud communication. This multi-dimensional architecture allows machine data and other data types to be processed collaboratively across the network, significantly improving system expandability.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

4Measurement precision

If all data is processed centrally in the cloud, then analysis accuracy is improved, but operating expenses increase

Engineering Contradiction:
Improveanalysis accuracyVSAvoidoperating expenses
Core Design Contradiction:
Measurement precisionVSLoss of energy

Solution Approach 1:

The patent applies partial centralization where only certain data types or certain analysis tasks are performed in the cloud, while other data is processed locally at terminals. This partial action approach maintains sufficient analysis accuracy for critical functions while reducing the energy cost of transmitting and processing all data centrally.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentEP3133502B1Terminal device and method for cooperatively processing data
Publication Date: 2020.11.11 SAMSUNG ELECTRONICS CO LTD
  • EP3133502B1 patent drawingFigure 1A
  • EP3133502B1 patent drawingFigure 1B
  • EP3133502B1 patent drawingFigure 1C

AI summary

Provided are a terminal, a cloud apparatus, a method of analyzing, by a terminal, activities of a user, and a method of analyzing, by a cloud apparatus, activities of a user. The terminal for analyzing an external apparatus and activities of a user, the terminal includes: a communication interface unit configured to communicate with the external apparatus; a controller configured to obtain data used to predict the activities of the user and anonymize some of the obtained data, and provide the anonymized data and a remainder of the data, which is not anonymized, to the external apparatus through the communication unit; and a display unit configured to display notification information related to the activities of the user based on activity prediction data analyzed by the external apparatus by using the provided data.