Heatmap Analysis

The Heatmap Analysis use case provides an overview of pedestrian density and movement patterns in monitored spaces. By converting video analytics into visual heatmaps, operators can identify high-traffic areas, optimize layout, and improve safety.

Overview

Heatmap Analysis transforms person tracking data into color-coded occupancy maps. These maps reveal where people gather most frequently and how movement flows through the scene over time.

Technologies Used

YOLOv8 for person detection.
ByteTrack / Tracker for continuous movement tracking.
Aggregation Engine to accumulate presence data across frames.
React Dashboard for displaying heatmap overlays and statistics.

Workflow

Capture video frames from CCTV or camera feeds.
Detect and track people in each frame.
Accumulate location data for each tracked person over time.
Generate heatmaps showing high-occupancy and frequent movement paths.
Render visual overlays and summary metrics in the dashboard.

Use Cases

Retail store optimization: Identify crowded zones and optimize product placement.
Facility management: Improve space layout in offices, lobbies, or waiting areas.
Safety monitoring: Detect congested areas and maintain safe movement paths.
Event planning: Analyze attendee flow and optimize entry/exit routes.

Benefits

Data-driven layout changes: Understand how people use the space before making changes.
Better crowd control: Spot hotspots before they become congested.
Improved service placement: Place staff and resources where they are most needed.
Operational insights: Compare different times and days for trend analysis.

Best Practices

Position cameras to cover the full area of interest.
Run heatmap analysis over multiple time windows for accuracy.
Combine heatmaps with queue and crowd alerts for complete monitoring.
Use results to inform both short-term operations and long-term planning.