Smart Traffic Management System

System Overview

Smart traffic management reduces congestion by 20-40% through adaptive signal timing based on real-time traffic conditions.

Hardware Components

• ESP32-CAM: Vehicle detection with AI
• Inductive Loop Sensors: Vehicle presence
• Traffic Light Module: LED signals
• Raspberry Pi: Central controller
• LoRa: Intersection communication

Vehicle Detection

// ESP32-CAM vehicle counting
#include "esp_camera.h"
#include "tensorflow/lite/micro/micro_interpreter.h"

int detectVehicles() {
  camera_fb_t *fb = esp_camera_fb_get();
  
  // Run object detection model
  int vehicleCount = runDetection(fb->buf);
  
  return vehicleCount;
}

Traffic Light Control

Direction	Vehicle Count	Wait Time	Green Duration
North	15	120s	45s
South	8	90s	30s
East	22	150s	60s
West	5	60s	20s

Emergency Vehicle Priority

// Emergency vehicle detection
void checkEmergencyVehicle() {
  if (detectSiren() || receiveEmergencySignal()) {
    // Clear path for emergency vehicle
    setAllRed();
    delay(2000);
    setGreen(emergencyDirection);
    
    // Notify other intersections
    broadcastEmergencyAlert();
  }
}

AI Optimization

Machine learning predicts traffic patterns and optimizes signal timing:

• Historical traffic data analysis
• Weather impact consideration
• Special event handling
• Rush hour prediction