Visual Fog Computing System for Automated Data Offload

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Solution Overview

Problem

Existing approaches for gathering facts and evidence in visual computing are inefficient, requiring manual data collection from multiple sources, and lack an effective mechanism for identifying and utilizing electronic devices with relevant information.

Innovation Solution

The implementation of a visual fog computing system that leverages both cloud and edge resources to perform large-scale visual computing tasks efficiently, using a flexible design that supports ad-hoc queries and is highly scalable.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual data collection from multiple sources is used, then information can be gathered from various sources, but the process is inefficient and time-consuming

Engineering Contradiction:

Improveinformation gathering efficiencyVSAvoidtime for manual data collection

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

Electronic devices automatically perform data collection and upload operations without manual intervention. The system enables devices to self-identify, self-register, and autonomously upload relevant data when queried, eliminating the need for manual data gathering from each source.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

A centralized server acts as an intermediary between multiple electronic devices and users. The server manages device registration, stores device information, and coordinates data requests, enabling efficient automated information gathering across distributed devices without direct manual intervention.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If electronic devices are distributed across multiple entities, then device availability increases, but identification and data collection becomes more complex

Engineering Contradiction:

Improvedevice source diversityVSAvoiddata collection mechanism complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The server implements a universal data collection mechanism that handles multiple device types and owners through a single standardized interface. The system uses common protocols for device registration, querying, and data upload, enabling diverse devices from different entities to be managed uniformly without increasing system complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system changes the state of device information from distributed and hidden to centralized and accessible. By storing device identifiers and capabilities in a centralized database on the server, the system transforms the complexity of identifying distributed devices into a simple database lookup operation.

Inventive Principle:

Principle #35Parameter changes

3Power

If cloud resources alone are used for visual computing, then processing power is sufficient, but latency increases and resource utilization decreases

Engineering Contradiction:

Improveprocessing powerVSAvoidprocessing latency

Core Design Contradiction:

PowerVSLoss of time

Solution Approach 1:

The system segments visual computing tasks between edge devices and cloud resources. Electronic devices at the edge perform initial data collection and local processing, then upload only relevant results to the cloud for further processing. This segmentation reduces the amount of data transmitted and processed centrally, lowering latency while maintaining adequate processing power.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system adds a spatial dimension to resource utilization by distributing computing across multiple levels: local edge devices for immediate processing and cloud resources for comprehensive analysis. This multi-dimensional architecture enables parallel processing at different locations, reducing overall processing time while optimizing resource utilization across the distributed system.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

4Reliability

If data is stored locally on electronic devices, then data availability is maintained, but storage capacity is limited

Engineering Contradiction:

Improvedata availabilityVSAvoiddevice storage capacity

Core Design Contradiction:

ReliabilityVSVolume of stationary object

Solution Approach 1:

The system extracts data from local device storage and transfers it to centralized server storage. Electronic devices maintain minimal local storage for operational data, while the server provides extensive storage capacity for collected evidence and information. This extraction resolves the contradiction by moving bulk storage to the server while keeping devices available for data collection.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS12225131B2Data offload and time synchronization for ubiquitous visual computing witness

Publication Date: 2025.02.11 INTEL CORP

AI summary

In one embodiment, a road side unit (RSU) establishes a data offload session with a vehicle in the vicinity of the RSU based on a session establishment request sent by the vehicle, and stores data received from the vehicle during the data offload session in its memory. The RSU generates storage record information (including identifying information for the RSU) for the stored data, and transmits the storage record information to the vehicle.