Emergency People Evacuation System using Crowd Density Detection and Path Finding Algorithm

A complex process, crowd evacuation involves a variety of human behaviours like evacuation motion and behavioural response. Most injuries or losses are not caused by the crises or disasters themselves. Instead, sudden actions like stampedes, shoving people aside, knocking people over, and trampling people over result in fatalities. The logicalness of architectural design, safety management, and the prevention or reduction of fatalities in crises can all be improved by well-organized crowd evacuations. In emergency situations, CCTV footage creates dim, blurry images that make it challenging to evacuate crowds. The bottleneck effect at emergency exits is a significant result of the current models and simulation systems for crowd evacuation based on the Ant Colony Optimization algorithm. By combining low illumination video image enhancement algorithm and CS RNet crowd density estimation model, a faster crowd evacuation can be done during emergency situations.