Computer Vision Automation Steps for Lower-Cost Surveillance Workflows

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Solution Overview

Problem

Current automated processes using computer vision for surveillance tasks are not widely available due to high research and development costs and time requirements, limiting their accessibility and efficiency.

Innovation Solution

A computer vision process processing method and system that utilize computer vision automation step simulation components to simulate and execute various user operations on electronic devices without altering software or hardware environments, enabling efficient execution of complex automation steps.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If computer vision automation processes are developed to complete surveillance tasks, then automation capability and surveillance efficiency are improved, but research and development costs and time requirements increase significantly

Engineering Contradiction:
Improveautomation capabilityVSAvoiddevelopment time
Core Design Contradiction:
Extent of automationVSLoss of time

Solution Approach 1:

The patent uses image copying and recognition to replicate human visual processing. The system captures images from cameras, copies them to memory, processes them through computer vision algorithms, and executes corresponding automation steps, thereby achieving automated surveillance without requiring complex custom development for each task

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The patent creates a universal computer vision processing system that can handle multiple surveillance tasks through a single integrated platform. The system processes various types of images (from different cameras, resolutions, formats) and executes diverse automation steps (monitoring, detection, tracking) using common processing circuits and algorithms, reducing the need for separate specialized systems for each function

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

2Extent of automation

If computer vision automation processes are developed to complete surveillance tasks, then automation capability is improved, but research and development costs increase significantly

Engineering Contradiction:
Improveautomation capabilityVSAvoiddevelopment cost
Core Design Contradiction:
Extent of automationVSEase of manufacture

Solution Approach 1:

The system employs self-service mechanisms where the computer vision processing circuit automatically captures images, processes them, and executes automation steps without requiring manual intervention or complex programming for each specific task. The automated image processing and event recognition systems perform surveillance functions autonomously, reducing the need for expensive custom development and specialized expertise

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The patent utilizes parameter changes in image processing to achieve versatile automation. By adjusting parameters such as image resolution, frame rate, detection sensitivity, and processing speed, the system can adapt to different surveillance scenarios without requiring redevelopment. This allows cost-effective deployment across various applications by simply modifying processing parameters rather than rewriting software

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentUS20260003492A1Computer vision process processing method and computer vision process processing system
Publication Date: 2026.01.01 ISCOOLLAB CO LTD
  • US20260003492A1 patent drawing
  • US20260003492A1 patent drawing
  • US20260003492A1 patent drawing

AI summary

A computer vision process processing method and a computer vision process processing system are provided. The computer vision process processing method includes: obtaining a first image; and correspondingly determining one or more computer vision process events according to the first image and one or more computer vision automation steps. The one or more computer vision automation steps are each completed by using one or more computer vision automation step simulation components.