AI-Based Vehicle Speed Monitoring and Automatic Challan System

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AI-Based Vehicle Speed Monitoring & Automatic Challan System Using ESP32 + AI Agent + n8n Automation + Telegram Voice Alerts + Google Sheets + ThingSpeak Cloud
AI-Based Vehicle Speed Monitoring System

AI-Based Vehicle Speed Monitoring & Automatic Challan System

ESP32 + IoT + AI Agent + n8n + Telegram Voice Alerts + Google Sheets + ThingSpeak

1. Project Overview

This project is an AI-powered smart traffic monitoring system using ESP32, sensors, cloud dashboard, automation workflows, and Telegram alerts.

  • Vehicle Speed Detection
  • Automatic Challan Generation
  • Telegram Notifications
  • Voice Alerts
  • Google Sheets Logging
  • ThingSpeak Cloud Dashboard
  • AI Power Consumption Prediction

2. Components List

Component Quantity Purpose
ESP32 1 Main Controller
IR Sensors 2 Vehicle Detection
Buzzer 1 Alert Sound
OLED Display 1 Speed Display
LEDs 2 Status Indicators

3. Working Principle

Two IR sensors are placed at a fixed distance. When a vehicle crosses the first sensor, timer starts. When it crosses the second sensor, timer stops.

Speed Formula

Speed = Distance / Time

Speed(km/h) = (Distance / Time) × 3.6

4. Circuit Connections

Component ESP32 Pin
IR Sensor 1 GPIO 14
IR Sensor 2 GPIO 27
Buzzer GPIO 26
Green LED GPIO 25
Red LED GPIO 33

5. System Flowchart

START
   ↓
Initialize ESP32
   ↓
Connect WiFi
   ↓
Detect Vehicle
   ↓
Calculate Speed
   ↓
Speed > Limit?
   ↓
YES
   ↓
Send Alert to n8n
   ↓
Telegram Notification
   ↓
Voice Alert
   ↓
Google Sheets Update
   ↓
ThingSpeak Upload
   ↓
END

6. ESP32 Source Code

#include <WiFi.h>
#include <HTTPClient.h>

const char* ssid = "YOUR_WIFI";
const char* password = "YOUR_PASSWORD";

String webhook = "YOUR_N8N_WEBHOOK_URL";

#define SENSOR1 14
#define SENSOR2 27

unsigned long startTime;
unsigned long endTime;

float distanceMeters = 1.0;

bool trigger = false;

void setup() {

  Serial.begin(115200);

  pinMode(SENSOR1, INPUT);
  pinMode(SENSOR2, INPUT);

  WiFi.begin(ssid, password);

  while(WiFi.status() != WL_CONNECTED){
    delay(1000);
    Serial.println("Connecting...");
  }

  Serial.println("WiFi Connected");
}

void loop() {

  if(digitalRead(SENSOR1)==LOW && !trigger){

      startTime = millis();
      trigger = true;
  }

  if(digitalRead(SENSOR2)==LOW && trigger){

      endTime = millis();

      float timeSec = (endTime - startTime)/1000.0;

      float speed = (distanceMeters/timeSec)*3.6;

      Serial.println(speed);

      if(speed > 40){

          sendData(speed);
      }

      trigger = false;
  }
}

void sendData(float speed){

    HTTPClient http;

    http.begin(webhook);

    http.addHeader("Content-Type","application/json");

    String data = "{\"speed\":\""+String(speed)+"\"}";

    http.POST(data);

    http.end();
}

7. n8n Workflow

Webhook
   ↓
Check Speed Limit
   ↓
Telegram Alert
   ↓
Voice Notification
   ↓
Google Sheets Update
   ↓
ThingSpeak Upload

8. Telegram Bot Setup

  1. Open Telegram
  2. Search BotFather
  3. Create new bot using /newbot
  4. Copy Bot Token
  5. Get Chat ID

9. Google Sheets Integration

Time Speed Fine Status
10:30 AM 72 km/h ₹1000 Overspeed

10. ThingSpeak Cloud Dashboard

Upload sensor data to ThingSpeak cloud dashboard for:

  • Real-Time Speed Monitoring
  • Traffic Analytics
  • Power Consumption Tracking
  • Violation Statistics

11. AI Power Consumption Prediction

Predicted Power =
(sensor_time × current) +
(wifi_time × current)

AI predicts traffic load and controls ESP32 sleep mode for power optimization.

12. Voice Notification Automation

Telegram voice alerts are generated using:

  • Google Text-to-Speech
  • ElevenLabs API
Warning!
Overspeed vehicle detected.
Speed exceeded legal limit.
Automatic challan generated.

13. Automatic Challan Logic

Speed Range Fine Amount
40-60 km/h ₹500
60-80 km/h ₹1000
80+ km/h ₹2000

14. Future Enhancements

  • Number Plate Recognition
  • ESP32-CAM Integration
  • AI Traffic Prediction
  • Smart City Dashboard
  • Cloud AI Analytics
  • GPS Tracking

15. Deployment Guide

  1. Install sensors roadside
  2. Connect ESP32 to WiFi
  3. Deploy n8n workflow
  4. Configure Telegram bot
  5. Connect Google Sheets
  6. Setup ThingSpeak dashboard
  7. Test vehicle detection

16. Estimated Project Cost

Item Cost
ESP32 ₹500
Sensors ₹300
Display ₹250
Miscellaneous ₹500

Total Cost: ₹1500 - ₹2500

17. Conclusion

This AI-powered IoT project combines ESP32, automation workflows, Telegram notifications, AI analytics, and cloud dashboards to create an intelligent traffic monitoring and automatic challan system for smart cities.

AI-Based Vehicle Speed Monitoring System | ESP32 + AI + IoT + n8n

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