VisionAIre
  • About Nodeflux
  • Visionaire Stream
    • Overview
    • Requirements
      • Credential Keys
      • Tested Hardware
      • Bandwith Requirements
    • Installation Guide
      • Dependencies
      • Simple Installation
      • Advanced Installation
      • Clustering Installation
      • Add-ons Analytics Installation
        • People Attributes Installation
        • Vehicle Attributes Installation
        • OVOD Installation
        • OVIC Installation
        • VM Installation
        • VLM Installation
    • Analytics
      • Face Recognition
        • Additional Information
          • Overview
          • Disclaimer
          • Metrics
          • Testing
      • People Analytics
      • Crowd Estimation
      • PPE Detection
      • License Plate Recognition
      • Vehicle Analytics
      • Water Level Monitoring
        • Camera Guideline
      • Pre-Flood Monitoring
      • Person Smoking Detection
      • Person with Handphone Detection
      • Smoke and Fire Detection
      • Person Using Firearms Detection
      • Vandalism Attempt Recognition
      • ATM Burglary Incident Recognition
      • Road Crash Monitoring
      • People Fighting Recognition
      • Riot Recognition
    • Developer Guide
      • How our APIs work
      • HTTP APIs
      • Websocket
      • Database Structure
    • Changelogs
  • Visionaire Snapshot
    • Overview
    • Requirements
    • Installation Guide
      • Face Searching & Matching
        • Single Node
        • Clustering
      • Helmet Detection
      • Chicken Estimation
      • Face Detection
      • Over Dimension Over Load
      • Frontal License Plate Recognition
    • Analytics
      • Face Searching & Matching
        • Face Enrollment
          • Image Guideline
          • Face and Image Quality Assessment
            • Setup On Premise
            • API
          • Insert / Update / Delete Enrollment
          • Batch Enrollment
      • Helmet Detection
      • Chicken Estimation
      • People Demography
      • Face Detection
      • Over Dimension Over Load
      • License Plate Recognition -Frontal
    • Developer Guide
      • APIs
        • Face Searching & Matching
        • Helmet Detection
        • Chicken Estimation
        • People Demography
        • Face Detection
        • Over Dimension Over Load
        • Frontal License Plate Recognition
      • Vanilla APIs for Face Enrollment
      • Porting Enrollment Database Cluster to Docker
    • Changelogs
  • VisionAIre Dashboard
    • Introduction
    • Add Analytic Assignment
    • Accessing Vanilla Database
    • Connect to Vanilla Websocket
    • Create your own visualization
      • Migration from Old Streamer to New Streamer
      • Drawing Region of Interest
      • Additional Visualization Query
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  1. Visionaire Stream
  2. Installation Guide

Add-ons Analytics Installation

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Last updated 11 months ago

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This diagram outlines the integrated workflow of VisionAIre's add-on concept. The process begins with the VisionAIre Stream platform, which captures live CCTV footage and uses advanced AI models for initial analysis. This platform will send images from the stream AI model. These images are then sent to the VisionAIre Snapshot platform, which acts as an add-on service, providing a more granular level of analysis. The Snapshot platform is equipped with sophisticated AI model capabilities to attribute detailed characteristics to individuals detected in the footage, enriching the data for comprehensive analytics.

Furthermore, the VisionAIre Stream platform takes charge of the entire licensing process, negating the necessity for distinct licenses for each service. This unified approach ensures that users can access both the Stream and Snapshot platforms without the administrative burden of managing multiple licenses, resulting in a streamlined user experience.

To install OVOD Service please check here:

To install OVIC service please check here:

To install People Attributes service, please check here:

OVOD Installation
OVIC Installation
People Attributes Installation
Diagram to explain how add-ons concept works
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