People Heatmap
Computer Vision / Python / OpenCV / Numpy

The People Heatmap project leverages computer vision to map areas with the highest foot traffic, providing a clear visual representation of frequently used paths within busy environments. By identifying these routes, the People Heatmap offers invaluable data for designing more efficient, customer-friendly spaces in venues like shopping malls, airports, and public squares.

Through advanced computer vision techniques, the People Heatmap continuously analyzes crowd movement, revealing trends in visitor behavior over time. For example, it highlights which corridors or entrances see the most use in a shopping mall, or which paths are most popular in airport terminals. This dynamic data helps facility managers and business owners make informed decisions to improve accessibility, optimize signage, and even enhance crowd flow during peak times.

With the insights provided by People Heatmap, spaces can be tailored to better meet the needs of customers, creating smoother, more enjoyable experiences. In emergency situations, this heatmap data can also support safe and efficient evacuation planning by showing potential bottlenecks and less-trafficked escape routes.

In all high-traffic spaces, People Heatmap stands out as a powerful tool for crafting intelligently designed environments that prioritize customer satisfaction, safety, and operational efficiency. This technology marks a step forward in the creation of truly smart, responsive spaces.

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