Built a local AI video analytics PoC for scene-level event analysis (YOLO26)
I built a local AI video analytics PoC that analyzes uploaded videos and generates structured reports from the scene.
The system focuses on scene-level understanding rather than only basic object detection. It can report signals such as people density, movement patterns, zone activity, crossing behavior, forgotten-item candidates, and safety-event candidates like fall or lying-still behavior.
The goal was to create a review-oriented workflow where the system highlights possible events, generates a risk score, and produces visual/report-based outputs for human review.
It does not make final security decisions. The detected events are treated as candidate signals that should be reviewed by an operator.
For the test workflow, I intentionally used mixed video scenes to evaluate how the system handles pedestrian flow, object-related events, safety-event candidates, and scene transitions. Optional portfolio link : www.linkedin.com/in/brkndc