ALL & ChangeD DATA-Driven

Image Analysis: Full Data AI Analysis vs. Change-Triggered Urgent Response

This diagram illustrates a system architecture comparing two core strategies for data processing.

🎯 Core 1: Two Data Processing Approaches

Approach A: Full Data Processing (Analysis)

  • All Data path (blue)
  • Collects and comprehensively analyzes all data
  • Performs in-depth analysis through Deep Analysis
  • AI-powered statistical change (Stat of changes) analysis
  • Characteristics: Identifies overall patterns, trends, and correlations

Approach B: Separate Change Detection Processing

  • Change Only path (yellow)
  • Selectively detects only changes
  • Extracts and processes only deltas (differences)
  • Characteristics: Fast response time, efficient resource utilization

πŸ”₯ Core 2: Analysisβ†’Urgent Responseβ†’Expert Processing Flow

Stage 1: Analysis

  • Full Data Analysis: AI-based Deep Analysis
  • Change Detection: Change Only monitoring

Stage 2: Urgent Response (Urgent Event)

  • Immediate alert generation when changes detected (⚠️ Urgent Event)
  • Automated primary response process execution
  • Direct linkage to Work Process

Stage 3: Expert Processing (Expert Make Rules)

  • Human expert intervention
  • Integrated review of AI analysis results + urgent event information
  • Creation and modification of situation-appropriate rules
  • Work Process optimization

πŸ”„ Integrated Process Flow

[Data Collection] 
    ↓
[Path Bifurcation]
    β”œβ”€β†’ [All Data] β†’ [Deep Analysis] ─┐
    β”‚                                  β”œβ†’ [AI Statistical Analysis]
    └─→ [Change Only] β†’ [Urgent Event]β”€β”˜
                            ↓
                    [Work Process] ↔ [Expert Make Rules]
                            ↑_____________↓
                         (Feedback loop with AI)

πŸ’‘ Core System Value

  1. Dual Processing Strategy: Stability (full analysis) + Agility (change detection)
  2. 3-Stage Response System: Automated analysis β†’ Urgent process β†’ Expert judgment
  3. AI + Human Collaboration: Combines AI analytical power with human expert judgment
  4. Continuous Improvement: Virtuous cycle where expert rules feed back into AI learning

This system is an architecture optimized for environments where real-time response is essential while expert judgment remains critical (manufacturing, infrastructure operations, security monitoring, etc.).


Summary

  1. Dual-path system: Comprehensive full data analysis (stability) + selective change detection (speed) working in parallel
  2. Three-tier response: AI automated analysis triggers urgent events, followed by work processes and expert rule refinement
  3. Human-AI synergy: Continuous improvement loop where expert knowledge enhances AI capabilities while AI insights inform expert decisions

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