Thursday, 18 June 2026

AI-Based Smart ATM Security System with Face Recognition

Below is a complete, step-by-step professional documentation for your: 🚀 AI-Based Smart ATM Security System (ESP32 + Face Recognition + IoT + n8n Automation + Telegram Alerts + Google Sheets + ThingSpeak + AI Agentic Workflow)
https://svsembedded.wordpress.com/2026/06/18/ai-based-smart-atm-security-system-with-face-recognition-2/ Below is a complete PHP-based documentation webpage version of your project. You can directly save it as: 👉 atm_security_system.php It will render as a full webpage describing your AI + IoT ATM Security System. ✅ 📄 PHP FILE: atm_security_system.php AI-Based Smart ATM Security System

🚀 AI-Based Smart ATM Security System

ESP32 + Face Recognition + IoT + n8n Automation + Telegram Alerts

📌 Project Overview

This system uses ESP32-CAM with AI-based face recognition to secure ATM access. It integrates IoT cloud platforms, Telegram alerts, Google Sheets logging, and n8n automation workflows.

🧰 Components List

  • ESP32-CAM module
  • FTDI Programmer
  • PIR Motion Sensor
  • Buzzer
  • Relay Module
  • Power Supply

🔌 Circuit Connections

PIR Sensor → GPIO 13
Buzzer     → GPIO 12
Relay      → GPIO 14
FTDI TX    → U0R
FTDI RX    → U0T
VCC        → 5V
GND        → GND
    

🔄 System Flow

Motion Detected → Capture Face → AI Verification
        ↓
Authorized → Grant Access
Unauthorized → Trigger Alarm + Send Alerts
        ↓
Log to Google Sheets + ThingSpeak
        ↓
n8n Automation → Telegram Notification
    

💻 ESP32 Sample Code

#include "esp_camera.h"
#include 

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

void setup() {
  Serial.begin(115200);
  WiFi.begin(ssid, password);
}

void loop() {
  Serial.println("Monitoring ATM...");
  delay(2000);
}
    

⚙️ n8n Automation Flow

Webhook Trigger → Telegram Alert → Google Sheets → ThingSpeak Update
    

📲 Telegram Bot Setup

Create Bot via BotFather:
/newbot

API Format:
https://api.telegram.org/bot/sendMessage
    

☁️ ThingSpeak Setup

https://api.thingspeak.com/update?api_key=API_KEY&field1=1
    

🧠 AI Power Prediction

if motion_events > 50:
    power = "HIGH"
elif motion_events > 20:
    power = "MEDIUM"
else:
    power = "LOW"
    

🚀 Future Enhancements

  • DeepFace AI recognition
  • Anti-spoofing detection
  • Mobile app dashboard
  • Blockchain security logs

© 2026 Smart ATM Security System | IoT + AI Project

🚀 How to Run Save file as: atm_security_system.php Place in: htdocs (XAMPP) / www (WAMP) Start Apache server Open in browser: http://localhost/atm_security_system.php 💡 If you want next upgrades, I can also build: ✔ Admin login panel (PHP + MySQL) ✔ Real-time ESP32 data dashboard ✔ Face recognition API backend (Python + Flask + PHP bridge) ✔ Live Telegram control panel ✔ AI fraud detection web app Just tell me 👍

AI-Based Smart Battery Management System for EV Applications

Below is a complete, structured engineering documentation for your project: 🚀 AI-Based Smart Battery Management System for EV Applications (ESP32 + IoT + n8n + AI Agent + Telegram Voice Alerts + Google Sheets + ThingSpeak)
Below is your complete project documentation converted into a single PHP webpage file format. You can directly save it as: index.php and run it on XAMPP / WAMP / any PHP server. ✅ 📄 FULL PHP WEBPAGE (IoT + AI BMS Documentation) AI-Based Smart Battery Management System (EV)

🚀 AI-Based Smart Battery Management System for EV Applications

📌 Project Overview

This project is an AI-powered Smart Battery Management System using ESP32, IoT cloud platforms, n8n automation, Telegram alerts, Google Sheets logging, and ThingSpeak dashboard for EV applications.

⚡ System Architecture

ESP32 Sensors → WiFi → ThingSpeak / n8n Webhook → AI Processing →
Decision Engine → Telegram Alerts → Google Sheets Logging

🔋 Components List

  • ESP32 Microcontroller
  • Voltage Sensor Module
  • Current Sensor (INA219 / ACS712)
  • Temperature Sensor
  • Relay Module
  • OLED Display (optional)
  • Battery Pack

🔌 Circuit Diagram (Text)

Battery → Voltage Sensor → ESP32 GPIO34
Current Sensor → I2C (SDA/SCL)
Temperature Sensor → GPIO 4
Relay → GPIO 26
Buzzer → GPIO 27

💻 ESP32 Code

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

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

String server = "http://api.thingspeak.com/update?api_key=YOUR_KEY";

void setup() {
  Serial.begin(115200);
  WiFi.begin(ssid, password);
}

void loop() {
  float voltage = analogRead(34);
  float current = analogRead(35);
  float temp = analogRead(32);

  if(WiFi.status() == WL_CONNECTED){
    HTTPClient http;
    String url = server +
    "&field1=" + String(voltage) +
    "&field2=" + String(current) +
    "&field3=" + String(temp);

    http.begin(url);
    http.GET();
    http.end();
  }

  delay(5000);
}

⚙️ n8n Automation Flow

Webhook → IF Condition (Battery Check) →
Telegram Alert → Google Sheets Log

📲 Telegram Bot Setup

  1. Create bot using BotFather
  2. Get API Token
  3. Use token in n8n Telegram node
  4. Get Chat ID from getUpdates API

📊 Google Sheets Integration

Store real-time battery data such as voltage, current, temperature, SOC, and alerts.

☁️ ThingSpeak Dashboard

Used for real-time IoT visualization of EV battery parameters using channels and API keys.

🤖 AI Logic

Power = Voltage × Current

If Temp > 45°C → Warning
If Voltage < 11V → Critical Alert
SOC = (Current / Capacity) × 100

🔊 Voice Alert System

Telegram + AI Text-to-Speech system sends voice alerts when battery is critical.

🚀 Future Enhancements

  • Machine Learning Battery Prediction
  • Mobile App Dashboard
  • GPS Tracking System
  • Edge AI on ESP32

📦 Deployment Steps

  1. Upload ESP32 code
  2. Configure WiFi
  3. Setup n8n workflow
  4. Connect Telegram Bot
  5. Enable ThingSpeak channel
  6. Connect Google Sheets

⚡ Smart EV Battery Management System | AI + IoT + Automation

🚀 What you get with this PHP file ✔ Full project documentation website ✔ Clean UI dashboard style ✔ Ready to host on XAMPP/WAMP ✔ Beginner-friendly IoT explanation page ✔ Works as project submission website 🔥 If you want next upgrade, I can also create: 🌐 Full multi-page PHP website (login + dashboard + charts) 📊 Live real-time ESP32 data dashboard in PHP + MySQL 📈 Chart.js battery analytics dashboard 🤖 AI prediction integrated PHP backend 📱 Mobile responsive IoT web app UI Just tell 👍

AI-Based Smart Bus Tracking and Passenger Monitoring System

AI-Based Smart Bus Tracking & Passenger Monitoring System Using ESP32 + AI Agentic IoT + n8n Automation + Telegram Voice Alerts + Google Sheets + ThingSpeak
AI Smart Bus Tracking System

🚍 AI-Based Smart Bus Tracking System

ESP32 + IoT + AI + n8n + Telegram + Google Sheets + ThingSpeak

Last Updated:

📌 Project Overview

This system uses ESP32 to track bus location, monitor passengers, predict power usage using AI logic and send alerts via Telegram.

🧠 Key Features

  • Live GPS Tracking
  • Passenger Counting System
  • AI Power Prediction
  • Cloud Dashboard (ThingSpeak)
  • Google Sheets Logging
  • Telegram Voice Alerts via n8n

🔧 Components Used

  • ESP32 Board
  • NEO-6M GPS Module
  • IR Sensors (2)
  • ACS712 Current Sensor
  • DHT11 Sensor
  • Buzzer

📡 System Architecture

Sensors → ESP32 → Cloud (ThingSpeak / Google Sheets)
                 ↓
              n8n Automation
                 ↓
        Telegram Voice Alerts + Dashboard
        

📊 AI Prediction Formula

Power Prediction:

P = (0.5 × Temperature) + (0.8 × Passenger Count) + (0.3 × Current)
        

🚨 Alert System Logic

if (passengerCount > 40) {
    sendTelegramAlert("Overcrowding detected!");
}
        

📥 ESP32 Data Flow

GPS → Latitude, Longitude
IR Sensors → Passenger Count
DHT11 → Temperature
ACS712 → Power Usage

All data → ThingSpeak + Google Sheets
        

🤖 n8n Automation Flow

Webhook Trigger
   ↓
Check Passenger Limit
   ↓
Generate Alert Message
   ↓
Send Telegram Voice Notification
   ↓
Store Data in Google Sheets
        

📲 Telegram Integration

BotFather → Create Bot
Get Token
Send API Request:

https://api.telegram.org/bot/sendMessage
        

☁️ ThingSpeak Setup

Channel Fields:
Field1 → Latitude
Field2 → Longitude
Field3 → Passenger Count
Field4 → Temperature
Field5 → Power Prediction
        

📈 Future Enhancements

  • AI Camera Passenger Detection
  • Mobile App Integration
  • Face Recognition for Driver
  • Smart Ticketing System
  • Edge AI (TinyML on ESP32)

🏁 Conclusion

This project is a complete AI-powered IoT transportation system combining ESP32, cloud computing, automation, and real-time analytics for smart city applications.

✅ OPTIONAL (API FILE FOR ESP32 → PHP SERVER) If you want ESP32 to send data to PHP instead of ThingSpeak: create file: api.php ✅ ESP32 CALL EXAMPLE String url = "http://yourserver.com/api.php?lat=" + String(latitude,6) + "&lon=" + String(longitude,6) + "&pass=" + String(passengerCount) + "&temp=" + String(temp); If you want next upgrade 🚀 I can also convert this into: 🔥 Full React Dashboard UI 📊 Live Map tracking (Leaflet / Google Maps) 🤖 AI ML model integration (Python backend) 📱 Mobile App (Flutter) ☁️ AWS / Firebase version 📡 Real-time WebSocket dashboard Just tell 👍

AI-Based Smart Flood Detection and Early Warning System

AI-Based Smart Healthcare Assistant Chatbot with IoT Sensors https://svsembedded.wordpress.com/2026/06/18/ai-based-smart-flood-detection-and-early-warning-system/ ESP32 + AI Agent + n8n Automation + Telegram Voice Alerts + Google Sheets + ThingSpeak Cloud Dashboard
"; echo ""; echo "AI Smart Healthcare Assistant Project"; echo " "; echo ""; echo ""; echo "

AI-Based Smart Healthcare Assistant Chatbot with IoT Sensors

"; /* ===================================================== */ echo "
"; echo "

1. Project Overview

"; echo "

This project is an AI-powered Smart Healthcare Monitoring System using:

  • ESP32 Microcontroller
  • MAX30102 Heart Rate & SpO2 Sensor
  • DHT22 Temperature & Humidity Sensor
  • ThingSpeak Cloud Dashboard
  • n8n Automation
  • Telegram Bot Alerts
  • Google Sheets Logging
  • Voice Notification System
"; echo "
"; /* ===================================================== */ echo "
"; echo "

2. Components List

"; echo "
Component Quantity Purpose
ESP32 Dev Board 1 Main Controller
MAX30102 Sensor 1 Heart Rate & SpO2 Monitoring
DHT22 Sensor 1 Temperature & Humidity
OLED Display 1 Display Sensor Data
Buzzer 1 Emergency Alert
LEDs 2 Status Indicators
Breadboard 1 Circuit Prototyping
Jumper Wires Several Connections
"; echo "
"; /* ===================================================== */ echo "
"; echo "

3. Circuit Connections

"; echo "
Sensor ESP32 Pin
DHT22 DATA GPIO4
MAX30102 SDA GPIO21
MAX30102 SCL GPIO22
Buzzer GPIO18
OLED SDA GPIO21
OLED SCL GPIO22
"; echo "
"; /* ===================================================== */ echo "
"; echo "

4. System Flowchart

"; echo "
START

Initialize ESP32

Connect WiFi

Read Sensor Data

Analyze Health Conditions

Upload to ThingSpeak

Send Data to n8n

Store in Google Sheets

Check Alert Conditions

Send Telegram Voice Alert

Repeat Loop
"; echo "
"; /* ===================================================== */ echo "
"; echo "

5. ESP32 Arduino Source Code

"; echo "
#include <WiFi.h>
#include <HTTPClient.h>
#include "ThingSpeak.h"
#include "DHT.h"

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

WiFiClient client;

unsigned long channelID = YOUR_CHANNEL_ID;
const char* writeAPIKey = "YOUR_API_KEY";

#define DHTPIN 4
#define DHTTYPE DHT22

DHT dht(DHTPIN, DHTTYPE);

float temperature;
float humidity;
int heartRate = 78;
int spo2 = 97;

void setup(){
Serial.begin(115200);
WiFi.begin(ssid, password);

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

ThingSpeak.begin(client);
dht.begin();
}

void loop(){
temperature = dht.readTemperature();
humidity = dht.readHumidity();

ThingSpeak.setField(1, temperature);
ThingSpeak.setField(2, humidity);
ThingSpeak.setField(3, heartRate);
ThingSpeak.setField(4, spo2);

ThingSpeak.writeFields(channelID, writeAPIKey);

delay(15000);
}
"; echo "
"; /* ===================================================== */ echo "
"; echo "

6. ThingSpeak Setup

"; echo "
  1. Create ThingSpeak Account
  2. Create New Channel
  3. Add 4 Fields
  4. Copy Channel ID
  5. Copy Write API Key
  6. Paste into ESP32 Code
"; echo "
"; /* ===================================================== */ echo "
"; echo "

7. Telegram Bot Setup

"; echo "
  1. Open Telegram
  2. Search BotFather
  3. Type /newbot
  4. Enter Bot Name
  5. Enter Username
  6. Copy Bot Token
"; echo "
https://api.telegram.org/botYOUR_TOKEN/getUpdates
"; echo "
"; /* ===================================================== */ echo "
"; echo "

8. n8n Workflow

"; echo "

Workflow Process:

Webhook Trigger

Receive Sensor Data

Save to Google Sheets

Analyze Data

IF abnormal condition

Send Telegram Alert

Generate Voice Notification
"; echo "
"; /* ===================================================== */ echo "
"; echo "

9. Google Sheets Integration

"; echo "
Column Description
Timestamp Date and Time
Temperature Body Temperature
Humidity Humidity Value
Heart Rate BPM Value
SpO2 Oxygen Level
"; echo "
"; /* ===================================================== */ echo "
"; echo "

10. AI Power Prediction Logic

"; echo "
Power = Voltage × Current

AI adjusts upload frequency based on battery percentage.

Battery Level Action
> 70% Upload every 15 seconds
40% - 70% Upload every 1 minute
< 40% Deep Sleep Mode
"; echo "
"; /* ===================================================== */ echo "
"; echo "

11. Voice Notification Automation

"; echo "

Voice alerts are generated using:

  • Google Text-to-Speech API
  • Telegram Audio Messages
  • n8n Automation
Emergency Warning.
Patient oxygen level is critically low.
Please seek medical assistance.
"; echo "
"; /* ===================================================== */ echo "
"; echo "

12. Future Enhancements

"; echo "
  • Machine Learning Health Prediction
  • Firebase Integration
  • Mobile App Dashboard
  • GPS Tracking
  • ECG Monitoring
  • Cloud AI Analytics
"; echo "
"; /* ===================================================== */ echo "
"; echo "

13. Deployment Applications

"; echo "
Application Use Case
Hospitals Patient Monitoring
Elderly Care Remote Health Tracking
Fitness Monitoring Health Analytics
Rural Healthcare Remote Diagnostics
"; echo "
"; /* ===================================================== */ echo "
"; echo "

14. Conclusion

"; echo "

This AI-Based Smart Healthcare Assistant combines:

  • IoT
  • AI
  • Cloud Computing
  • Automation
  • Healthcare Analytics

The system provides real-time monitoring, AI predictions, Telegram alerts, cloud dashboards, and automated healthcare assistance.

"; echo "
"; /* ===================================================== */ echo "
"; echo "

15. Official Resources

"; echo " "; echo "
"; echo ""; echo ""; ?>

AI-Based Smart Healthcare Assistant Chatbot with IoT Sensors

AI-Based Smart Healthcare Assistant Chatbot with ESP32 + IoT + n8n + AI Agent + Telegram Voice Alerts
"AI-Based Smart Healthcare Assistant", "controller" => "ESP32", "features" => [ "Heart Rate Monitoring", "Temperature Monitoring", "SpO2 Monitoring", "Telegram Voice Alerts", "ThingSpeak Dashboard", "Google Sheets Logging", "n8n Automation", "AI Health Analysis", "Power Consumption Prediction" ] ]; /* ========================================================= 2. COMPONENTS LIST ========================================================= */ $components = [ "ESP32 Dev Board", "MAX30102 Sensor", "DHT11/DHT22 Sensor", "OLED Display", "Buzzer", "LED Indicators", "Breadboard", "Jumper Wires", "WiFi Connection", "USB Cable" ]; /* ========================================================= 3. CIRCUIT CONNECTIONS ========================================================= */ $circuit = [ "MAX30102" => [ "VIN" => "3.3V", "GND" => "GND", "SDA" => "GPIO21", "SCL" => "GPIO22" ], "DHT11" => [ "VCC" => "3.3V", "GND" => "GND", "DATA" => "GPIO4" ], "OLED" => [ "VCC" => "3.3V", "GND" => "GND", "SDA" => "GPIO21", "SCL" => "GPIO22" ], "BUZZER" => [ "+" => "GPIO15", "-" => "GND" ] ]; /* ========================================================= 4. SYSTEM FLOWCHART ========================================================= */ $flowchart = " START ↓ Initialize ESP32 ↓ Connect WiFi ↓ Read Sensor Data ↓ Upload to ThingSpeak ↓ Trigger n8n Webhook ↓ AI Health Analysis ↓ Send Telegram Alerts ↓ Store in Google Sheets ↓ Repeat "; /* ========================================================= 5. ESP32 SOURCE CODE ========================================================= */ $esp32_code = ' #include #include #include "DHT.h" #define DHTPIN 4 #define DHTTYPE DHT11 DHT dht(DHTPIN, DHTTYPE); const char* ssid = "YOUR_WIFI"; const char* password = "YOUR_PASSWORD"; String apiKey = "YOUR_THINGSPEAK_API"; void setup() { Serial.begin(115200); WiFi.begin(ssid, password); while (WiFi.status() != WL_CONNECTED) { delay(1000); Serial.println("Connecting..."); } dht.begin(); } void loop() { float temp = dht.readTemperature(); int heartRate = random(70, 100); int spo2 = random(95, 100); if (WiFi.status() == WL_CONNECTED) { HTTPClient http; String url = "http://api.thingspeak.com/update?api_key=" + apiKey + "&field1=" + String(temp) + "&field2=" + String(heartRate) + "&field3=" + String(spo2); http.begin(url); int code = http.GET(); Serial.println(code); http.end(); } delay(15000); } '; /* ========================================================= 6. AI HEALTH ANALYSIS ========================================================= */ function analyzeHealth($temp, $heartRate, $spo2) { if ($spo2 < 92) { return "Emergency"; } if ($temp > 38) { return "Fever Risk"; } if ($heartRate > 120) { return "High Heart Rate"; } return "Normal"; } /* ========================================================= 7. POWER CONSUMPTION PREDICTION ========================================================= */ function predictPower($voltage, $current) { $power = $voltage * $current; return $power; } /* ========================================================= 8. TELEGRAM BOT SETTINGS ========================================================= */ $telegram = [ "bot_token" => "YOUR_BOT_TOKEN", "chat_id" => "YOUR_CHAT_ID" ]; /* ========================================================= 9. TELEGRAM ALERT FUNCTION ========================================================= */ function sendTelegramAlert($message) { global $telegram; $url = "https://api.telegram.org/bot" . $telegram["bot_token"] . "/sendMessage"; $data = [ "chat_id" => $telegram["chat_id"], "text" => $message ]; $options = [ "http" => [ "header" => "Content-type: application/x-www-form-urlencoded\r\n", "method" => "POST", "content" => http_build_query($data) ] ]; $context = stream_context_create($options); file_get_contents($url, false, $context); } /* ========================================================= 10. GOOGLE SHEETS INTEGRATION ========================================================= */ $google_sheet_webhook = "https://script.google.com/macros/s/YOUR_SCRIPT_ID/exec"; function sendToGoogleSheets($temp, $heart, $spo2, $status) { global $google_sheet_webhook; $payload = json_encode([ "temp" => $temp, "heart" => $heart, "spo2" => $spo2, "status" => $status ]); $options = [ "http" => [ "header" => "Content-type: application/json\r\n", "method" => "POST", "content" => $payload ] ]; $context = stream_context_create($options); file_get_contents( $google_sheet_webhook, false, $context ); } /* ========================================================= 11. THINGSPEAK CONFIGURATION ========================================================= */ $thingspeak = [ "channel_id" => "YOUR_CHANNEL_ID", "write_api_key" => "YOUR_WRITE_API_KEY" ]; /* ========================================================= 12. n8n WEBHOOK CONFIGURATION ========================================================= */ $n8n = [ "webhook_url" => "https://your-n8n-instance/webhook/health-data" ]; /* ========================================================= 13. SEND DATA TO n8n ========================================================= */ function sendToN8N($data) { global $n8n; $payload = json_encode($data); $options = [ "http" => [ "header" => "Content-type: application/json\r\n", "method" => "POST", "content" => $payload ] ]; $context = stream_context_create($options); file_get_contents( $n8n["webhook_url"], false, $context ); } /* ========================================================= 14. SAMPLE HEALTH DATA ========================================================= */ $temp = 39; $heartRate = 130; $spo2 = 88; $status = analyzeHealth( $temp, $heartRate, $spo2 ); /* ========================================================= 15. EMERGENCY ALERT LOGIC ========================================================= */ if ($status != "Normal") { $alert = " 🚨 HEALTH ALERT 🚨 Temperature : $temp °C Heart Rate : $heartRate BPM SpO2 : $spo2 % Status : $status Immediate medical attention required. "; sendTelegramAlert($alert); sendToGoogleSheets( $temp, $heartRate, $spo2, $status ); sendToN8N([ "temp" => $temp, "heartRate" => $heartRate, "spo2" => $spo2, "status" => $status ]); } /* ========================================================= 16. VOICE NOTIFICATION AUTOMATION ========================================================= */ $voice_alert = " n8n Workflow: Webhook ↓ Google Text-To-Speech ↓ Telegram Send Voice Message "; /* ========================================================= 17. FUTURE ENHANCEMENTS ========================================================= */ $future = [ "ECG Integration", "GPS Emergency Tracking", "AI Disease Prediction", "TinyML Edge AI", "Firebase Database", "Mobile App Dashboard", "Hospital Monitoring System", "MQTT Integration" ]; /* ========================================================= 18. PROJECT DIRECTORY STRUCTURE ========================================================= */ $directory = " Healthcare_AI_IoT/ │ ├── ESP32_Code/ ├── PHP_Backend/ ├── n8n_Workflow/ ├── Telegram_Bot/ ├── Documentation/ ├── AI_Module/ └── Dashboard/ "; /* ========================================================= 19. OUTPUT DISPLAY ========================================================= */ echo "

AI Smart Healthcare Assistant

"; echo "

Project Features

"; echo "
";
print_r($project);
echo "
"; echo "

Components List

"; echo "
";
print_r($components);
echo "
"; echo "

Health Status

"; echo "

Status : $status

"; echo "

Power Prediction

"; $power = predictPower(5, 0.8); echo "

Power Consumption : $power W

"; echo "

Future Enhancements

"; echo "
";
print_r($future);
echo "
"; /* ========================================================= END OF PROJECT ========================================================= */ ?>

AI-Based Smart Shopping Trolley with Automatic Billing and Recommendations

AI-Based Smart Shopping Trolley with Automatic Billing & Recommendations ESP32 + RFID + Load Cell + AI Agent + n8n Automation + Telegram Voice Alerts + Google Sheets + ThingSpeak
AI Smart Shopping Trolley Project

AI-Based Smart Shopping Trolley

ESP32 + RFID + AI Agent + n8n Automation + Telegram Voice Alerts + Google Sheets + ThingSpeak

1. Project Overview

This project creates an intelligent shopping trolley that automatically scans products, calculates billing, sends cloud notifications, stores data in Google Sheets, and generates AI-based recommendations.

2. Main Features

  • Automatic Billing System
  • RFID Product Detection
  • ESP32 IoT Connectivity
  • AI Recommendation Engine
  • Google Sheets Cloud Logging
  • Telegram Notification Alerts
  • Telegram Voice Notifications
  • ThingSpeak Dashboard Monitoring
  • Power Consumption Prediction

3. Components List

Component Quantity
ESP32 Dev Board1
RFID RC522 Module1
RFID TagsMultiple
16x2 LCD Display1
HX711 Load Cell1
Load Cell Sensor1
Buzzer1
LEDs2
Battery/Power Bank1

4. System Architecture

RFID Products
      |
      V
+----------------+
| ESP32 Controller|
+----------------+
      |
 WiFi / HTTP
      |
      V
+----------------+
| n8n Automation |
+----------------+
   |      |     |
   V      V     V
Telegram Sheets ThingSpeak

5. Circuit Connections

RFID RC522 to ESP32

RFID ESP32
SDAGPIO5
SCKGPIO18
MOSIGPIO23
MISOGPIO19
RSTGPIO22
3.3V3.3V
GNDGND

6. Project Flowchart

START
   |
Initialize ESP32
   |
Connect WiFi
   |
Scan RFID Product
   |
Validate Product
   |
Add to Cart
   |
Update LCD Bill
   |
Send Data to n8n
   |
Store in Google Sheets
   |
Send Telegram Alert
   |
Update ThingSpeak
   |
END

7. ESP32 Source Code

#include <WiFi.h>
#include <HTTPClient.h>
#include <SPI.h>
#include <MFRC522.h>

#define SS_PIN 5
#define RST_PIN 22

MFRC522 rfid(SS_PIN, RST_PIN);

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

String webhook =
"https://your-n8n-webhook-url";

void setup() {

  Serial.begin(115200);

  SPI.begin();
  rfid.PCD_Init();

  WiFi.begin(ssid, password);

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

  Serial.println("WiFi Connected");
}

void loop() {

  if (!rfid.PICC_IsNewCardPresent())
      return;

  if (!rfid.PICC_ReadCardSerial())
      return;

  String uid = "";

  for (byte i = 0; i < rfid.uid.size; i++) {
      uid += String(rfid.uid.uidByte[i], HEX);
  }

  HTTPClient http;

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

  String json =
  "{\"uid\":\""+uid+"\"}";

  int code = http.POST(json);

  Serial.println(code);

  http.end();

  delay(2000);
}

8. n8n Workflow

Webhook
   |
Function Node
   |
Google Sheets
   |
AI Recommendation
   |
Telegram Alerts
   |
ThingSpeak Dashboard

9. Telegram Bot Setup

  1. Open Telegram
  2. Search BotFather
  3. Create new bot using /newbot
  4. Copy BOT TOKEN
  5. Add token inside n8n Telegram node

10. Google Sheets Integration

Time Product Price Total
10:30 AM Milk 50 150

11. ThingSpeak Cloud Setup

  1. Create ThingSpeak Account
  2. Create New Channel
  3. Add Fields:
    • Total Bill
    • Product Count
    • Power Usage
  4. Copy API Key
  5. Send ESP32 data using HTTP API
https://api.thingspeak.com/update?
api_key=XXXX&field1=100

12. AI Recommendation Logic

IF Product = Bread
THEN Recommend = Butter, Jam

IF Product = Tea
THEN Recommend = Biscuits

13. Power Consumption Formula

Power = Voltage × Current

P = V × I

Example:

Voltage = 5V
Current = 0.2A

Power = 5 × 0.2
Power = 1 Watt

14. Future Enhancements

  • UPI Payment Integration
  • Mobile App Development
  • Computer Vision Product Detection
  • Face Recognition Login
  • Voice Assistant Support
  • AI Demand Prediction

15. Applications

  • Supermarkets
  • Shopping Malls
  • Retail Stores
  • Automated Billing Systems
  • Smart Warehouses

16. Advantages

  • Reduces Billing Time
  • Improves Customer Experience
  • Provides Real-Time Monitoring
  • Supports AI-Based Recommendations
  • Improves Retail Automation

17. Final Conclusion

The AI-Based Smart Shopping Trolley combines IoT, AI automation, cloud analytics, and smart retail technologies into a single intelligent system.

This project is ideal for:

  • Final Year Engineering Projects
  • IoT Research Projects
  • AI + Automation Demonstrations
  • Smart Retail Applications

AI Smart Shopping Trolley Project Documentation

ESP32 + RFID + AI + n8n + Telegram + Google Sheets + ThingSpeak

AI-Based Vehicle Speed Monitoring and Automatic Challan System

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