• ASIFALI SALAUDDIN JAMADAR
• Bhoomika Sontanavar
• Deepa Kaloji
• Pranali Gawade
• Vinayak Jioji

Effective crowd regulation is essential in indoor environments to maintain safety, ensure comfort, and prevent congestion. Conventional monitoring methods depend heavily on human supervision, which can be unreliable and inefficient during high-traffic periods. This project introduces a smart and affordable Predictive Crowd Management System built around the ESP32-CAM module. The system performs automatic entry counting using camera-based motion detection, while an IR sensor positioned at the exit accurately records outgoing individuals. The live occupancy count is continuously updated and shown on an I2C LCD display. A predefined maximum capacity is programmed into the controller, and when this limit is exceeded, the system triggers a warning through an LED and buzzer, while a servo motor automatically closes the entry gate to prevent additional inflow. In addition, the ESP32-CAM hosts a web interface that provides real-time video streaming and status updates, enabling remote observation. Compact, low-cost, and easy to install, the system is suitable for applications in schools, retail stores, offices, libraries, and public event venues

ESP32-CAM, Crowd Management, IoT Monitoring, Human Detection, Automated Gate Control.

"PREDICTIVE CROWD MANAGEMENT SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 12, page no.c346-c352, December-2025, Available :http://www.jetir.org/papers/JETIR2512239.pdf

"PREDICTIVE CROWD MANAGEMENT SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 12, page no. ppc346-c352, December-2025, Available at : http://www.jetir.org/papers/JETIR2512239.pdf