How AI-powered heat map analytics transform raw video into actionable space utilization data for retail optimization, workplace planning, and facility management.
Heat map analytics aggregate person detection data over time to create visual representations of space utilization. High-traffic areas appear in warm colors (red, orange), while low-traffic zones appear in cool colors (blue, green). This simple visualization transforms hours of video into actionable spatial intelligence.
Unlike traditional people counting that provides entry/exit totals, heat maps show where people go within a space, how long they stay, and which paths they follow. This granularity enables decisions that aggregate foot traffic numbers alone cannot support.
Retail heat maps reveal customer navigation patterns through stores. Which aisles get the most traffic? Where do customers pause and browse? Which endcaps and promotional displays are actually seen? This data directly informs store layout, product placement, and promotional strategy.
Comparing heat maps across time periods (weekday vs weekend, morning vs evening, promotional periods vs normal) reveals behavioral patterns that inform staffing schedules, promotional timing, and seasonal layout adjustments.
Office heat maps help facilities teams optimize space allocation based on actual utilization rather than assumptions. Meeting rooms that show low usage can be repurposed. Common areas with high dwell times may need expansion. High-traffic corridors may benefit from wider pathways or better signage.
For hospitals and healthcare facilities, heat maps track staff and patient flow, identifying bottleneck areas in emergency departments, surgical suites, and outpatient clinics. This data supports evidence-based facility design and operational improvements.
Visylix generates heat maps by accumulating person detection centroids (the center point of each detected person) onto a spatial grid mapped to the camera's field of view. Perspective correction ensures that detections at different distances from the camera are weighted equally.
Heat maps can be generated for any time window: last hour, last day, last week, or custom ranges. Overlay views combine heat map data with the live camera feed, allowing operators to see real-time activity in context of historical patterns.