Codeproject Blue Iris Verified !!install!! -

: Confirm that Blue Iris is utilizing hardware decoding (Intel QuickSync or NVDEC) for video streams, leaving the GPU compute cores free for CodeProject.AI's matrix calculations.

However, based on common usage of that phrase:

: The system is highly adaptive, allowing users to process AI locally using a standard CPU, a dedicated NVIDIA GPU for faster speeds, or even a Google Coral AI chip to offload processing tasks. Strategic Deployment codeproject blue iris verified

The integration of CodeProject.AI Video Management Software (VMS) represents a pivotal shift from simple motion-based alerts to intelligent, verified event detection. By moving away from pixel-change triggers—which often produce false positives from shadows or rain—the system now uses a "verified" method where an AI server confirms the presence of specific objects before a user is notified. The Evolution of Verification

To make the AI efficient, you must configure how individual cameras trigger the AI analysis. Right-click a camera feed and select . Go to the Trigger tab and click Artificial Intelligence . : Confirm that Blue Iris is utilizing hardware

Running AI can be resource-intensive, especially on CPU-only systems.

: Download and install the CodeProject.AI Server (available as a Windows Service or Docker container). Go to the Trigger tab and click Artificial Intelligence

Just wanted to share that I’ve finally dialed in my Blue Iris setup with CodeProject.AI. After some trial and error with the "Confirmed" and "Verified" status in the alerts, I’m seeing near-zero false positives.

For optimal performance, CodeProject.AI requires significant resources.