01 Introduction
This project presents a real-time, low-cost hardware solution designed to manage crowd congestion in institutional mess facilities using bidirectional IR sensors.
02 Aim & Objectives
- Live Counting: Track real-time occupancy using affordable IR sensors.
- Smart Wait Time: Estimate dynamic waiting time based on actual exit rate.
- Overcrowding Alert: Notify students and staff when capacity thresholds are crossed.
- Dashboard Display: Real-time visualization on a web-based dashboard.
03 Working Principle
Step 1
Bidirectional Detection
Two IR sensors mounted at the entrance confirm entry/exit direction based on the sequence of triggering.
Step 2
Wait Time Algorithm
Estimated Wait = (Current Occupancy - Safe Threshold) / Average Exit Rate.
Step 3
Dashboard Sync
A Python script reads Serial data and updates a web dashboard for real-time visibility.
Components
Arduino Uno
Main microcontroller for sensor polling and logic.
IR Obstacle Sensors
Mounted for bidirectional entry/exit detection.
Python/Flask Backend
Processes data and serves the web dashboard.
Buzzer & LEDs
Physical indicators for current crowd levels.
Applications
College Mess & Canteens
Hospital OPD & Pharmacy queues
Banking & Government service centers
Retail & Transport hubs
Future Scope
- • Mobile app integration for remote tracking.
- • Predictive analytics for peak-hour suggestions.
- • Push notifications for crowd alerts.
- • Scalability to multi-door environments.