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Feature/spatial analytics documentation#597

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rawatts10 wants to merge 15 commits intomainfrom
feature/spatial-analytics-documentation
Closed

Feature/spatial analytics documentation#597
rawatts10 wants to merge 15 commits intomainfrom
feature/spatial-analytics-documentation

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📝 Description

This PR adds comprehensive developer documentation for working with SceneScape's spatial analytics data, focusing on ROIs (Regions of Interest) and Tripwires. The documentation provides complete guidance for building applications that consume spatial analytics events from SceneScape's sensor-agnostic platform.

What was changed:

  • Added working-with-spatial-analytics-data.md (872 lines) - complete developer guide for spatial analytics
  • Added sample_region_tripwire.png - visual example from Intel HQ Santa Clara parking lot

Why it was needed:

  • Developers need comprehensive documentation to understand and consume spatial analytics events
  • Real-world examples help developers understand practical deployment scenarios
  • The sensor-agnostic architecture benefits were not well documented
  • Authentication patterns for different deployment scenarios needed clarification

How the changes add value:

  • Provides complete tutorial with Python and JavaScript examples ready to run
  • Documents all event data structures with detailed field descriptions
  • Explains multi-sensor advantages and sensor-agnostic architecture
  • Includes Intel HQ parking lot example showing real-world ROI and tripwire deployment

✨ Type of Change

Select the type of change your PR introduces:

  • 🐞 Bug fix – Non-breaking change which fixes an issue
  • 🚀 New feature – Non-breaking change which adds functionality
  • 🔨 Refactor – Non-breaking change which refactors the code base
  • 💥 Breaking change – Changes that break existing functionality
  • 📚 Documentation update
  • 🔒 Security update
  • 🧪 Tests
  • 🚂 CI

🧪 Testing Scenarios

Describe how the changes were tested and how reviewers can test them too:

  • ✅ Tested manually
    • Verified all code examples work with SceneScape deployment
    • Tested Python scripts (discover.py, listen.py) with live MQTT events
    • Validated JavaScript web example with WebSocket MQTT connection
    • Confirmed image rendering and file structure
  • 🤖 Ran automated end-to-end tests

Manual Testing Details:

  • Environment setup instructions tested on Ubuntu
  • REST API examples validated against SceneScape deployment
  • MQTT authentication patterns verified for both WebSocket and direct protocols
  • All tutorial examples run successfully and produce expected output
  • Documentation formatting and internal links verified

✅ Checklist

Before submitting the PR, ensure the following:

  • 🔍 PR title is clear and descriptive
  • 📝 For internal contributors: If applicable, include the JIRA ticket number (e.g., ITEP-123456) in the PR title. Do not include full URLs
  • 💬 I have commented my code, especially in hard-to-understand areas
  • 📄 I have made corresponding changes to the documentation
  • ✅ I have added tests that prove my fix is effective or my feature works

Additional Notes:

  • This is purely a documentation enhancement with working code examples
  • All examples include detailed explanations and are ready for immediate use by developers
  • The Intel HQ example provides real-world context that makes the concepts immediately understandable
  • No configuration or infrastructure changes included

saratpoluri and others added 15 commits November 2, 2025 17:38
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Jakub Sikorski <jakub.sikorski@intel.com>
Fixes the issue of the GLB texture being missing when viewed in 3D UI.
This pull request refactors logging throughout the cluster_analytics codebase to improve log clarity and reduce noise in production logs. The main change is downgrading many log messages from info to debug level, especially those related to routine operations and parameter changes, while retaining info and error for significant events and errors. Additionally, more detailed error information is now logged at the debug level, and some log messages have been clarified or slightly reworded.
Create separate build and demo targets for building and deploying all services. The default targets are reserved for core containers.

Additional changes:
The mapping container's version is set in docker-compose.yml
mapping container health check executes and shows the health status correctly
This PR simplifies cluster analytics configuration by removing JSON-based configuration for tracking parameters and hardcoding them directly in the source code and removing not used tools from Dockerfile.
This PR aligns the generated mesh from mapping service to be in the first quadrant (+x and +y) and the rotation of the mesh is adjusted to have the floor plane flatter on the xy plane. The ortho/top-down view of the generated mesh i.e the thumbnail is properly rendered. The pose of all cameras is accurately reflected in scenescape.
Transform controls of cameras are hidden on load to avoid a cluttered 3D UI when many cameras are in a scene.
The colors of reconstructed mesh are muted due to insufficient lighting. Change the ambient light color and directional light intensity.
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8 participants