AI-Based Voice Controlled Industrial Automation System

AI-Based Voice Controlled Industrial Automation System ESP32 + AI Agent + n8n Automation + Telegram Voice Alerts + Google Sheets + ThingSpeak Cloud Dashboard

AI-Based Voice Controlled Industrial Automation System ESP32 + AI Agent + n8n Automation + Telegram Voice Alerts + Google Sheets + ThingSpeak Cloud Dashboard This project combines: Industrial automation using ESP32 Voice-controlled operation AI-based monitoring and prediction IoT cloud dashboard n8n workflow automation Telegram voice alert notifications Google Sheets data logging ThingSpeak live monitoring The system can: Monitor industrial parameters (temperature, gas, vibration, current, voltage) Control machines using voice commands Predict abnormal power usage Send voice alerts to Telegram Store data in Google Sheets Display live analytics on ThingSpeak Trigger AI-based automation actions 1. Project Overview Main Features ✅ Voice-controlled industrial equipment ✅ AI-powered power consumption prediction ✅ Real-time sensor monitoring ✅ ESP32 WiFi-based automation ✅ Telegram voice notification alerts ✅ Google Sheets logging ✅ ThingSpeak cloud analytics ✅ n8n automation workflows ✅ Remote monitoring dashboard ✅ Agentic AI decision making 2. System Architecture +----------------------+ | Voice Commands | | (Telegram / Web UI) | +----------+-----------+ | v +---------------------------------------------------+ | n8n Server | |---------------------------------------------------| | AI Agent Logic | | Telegram Bot | | Google Sheets Integration | | Voice Alert Generator | | Webhook Automation | +-------------------+-------------------------------+ | v +-------------------+ | ESP32 | |-------------------| | WiFi Connectivity | | Relay Control | | Sensor Monitoring | +---------+---------+ | v +----------------------------+ | Industrial Devices/Sensors | +----------------------------+ | v +----------------+ | ThingSpeak IoT | +----------------+ 3. Components Required Component Quantity Purpose ESP32 Dev Board 1 Main controller Relay Module (4-channel) 1 Machine control DHT22 Sensor 1 Temperature/Humidity ACS712 Current Sensor 1 Power monitoring MQ-2 Gas Sensor 1 Gas detection Vibration Sensor 1 Machine vibration OLED Display (Optional) 1 Local display Buzzer 1 Alarm Power Supply 5V/12V 1 System power Jumper Wires Several Connections Breadboard/PCB 1 Assembly WiFi Router 1 Internet connectivity 4. Circuit Schematic Diagram ESP32 Pin Connections Sensor/Module ESP32 Pin Relay IN1 GPIO 26 Relay IN2 GPIO 27 DHT22 Data GPIO 4 MQ2 Analog GPIO 34 ACS712 Output GPIO 35 Vibration Sensor GPIO 32 Buzzer GPIO 25 5. Working Principle Step-by-Step Process Step 1 — Sensor Data Collection ESP32 continuously reads: Temperature Humidity Current usage Gas leakage Vibration status Step 2 — WiFi Communication ESP32 sends sensor data to: ThingSpeak n8n webhook Google Sheets Step 3 — AI Analysis AI agent inside n8n: Predicts abnormal power consumption Detects machine anomalies Identifies unsafe conditions Step 4 — Automation Actions If abnormality detected: Relay OFF command Telegram alert sent Voice message generated Data stored in cloud Step 5 — Dashboard Monitoring User can monitor: Real-time charts Machine health Power usage Alerts history 6. Flowchart START | v Initialize ESP32 | Connect WiFi | Read Sensors | Send Data to n8n | Send Data to ThingSpeak | AI Analysis | Abnormal? / \ YES NO | | Send Alert | | Turn OFF Relay | | Telegram Voice Alert | Store Data in Google Sheets | Repeat Loop 7. ESP32 Source Code #include #include #include "DHT.h" #define DHTPIN 4 #define DHTTYPE DHT22 #define RELAY_PIN 26 #define MQ2_PIN 34 #define CURRENT_PIN 35 #define VIBRATION_PIN 32 #define BUZZER_PIN 25 DHT dht(DHTPIN, DHTTYPE); const char* ssid = "YOUR_WIFI_NAME"; const char* password = "YOUR_WIFI_PASSWORD"; String webhookURL = "YOUR_N8N_WEBHOOK_URL"; void setup() { Serial.begin(115200); pinMode(RELAY_PIN, OUTPUT); pinMode(BUZZER_PIN, OUTPUT); dht.begin(); WiFi.begin(ssid, password); while(WiFi.status() != WL_CONNECTED){ delay(1000); Serial.println("Connecting..."); } Serial.println("WiFi Connected"); } void loop() { float temp = dht.readTemperature(); float hum = dht.readHumidity(); int gas = analogRead(MQ2_PIN); int current = analogRead(CURRENT_PIN); int vibration = digitalRead(VIBRATION_PIN); Serial.println(temp); if(WiFi.status() == WL_CONNECTED){ HTTPClient http; http.begin(webhookURL); http.addHeader("Content-Type", "application/json"); String jsonData = "{"; jsonData += "\"temperature\":" + String(temp) + ","; jsonData += "\"humidity\":" + String(hum) + ","; jsonData += "\"gas\":" + String(gas) + ","; jsonData += "\"current\":" + String(current) + ","; jsonData += "\"vibration\":" + String(vibration); jsonData += "}"; int response = http.POST(jsonData); Serial.println(response); http.end(); } if(gas > 2500){ digitalWrite(RELAY_PIN, LOW); digitalWrite(BUZZER_PIN, HIGH); } else{ digitalWrite(RELAY_PIN, HIGH); digitalWrite(BUZZER_PIN, LOW); } delay(10000); } 8. Setting Up Arduino IDE Install Libraries Install: WiFi HTTPClient DHT sensor library Add ESP32 Board Open: File → Preferences Add board URL: https://dl.espressif.com/dl/package_esp32_index.json Install: ESP32 by Espressif Systems 9. n8n Automation Workflow Workflow Modules Nodes Used Node Purpose Webhook Receive ESP32 data IF Node Condition checking OpenAI/AI Agent Prediction Telegram Node Alert sending Google Sheets Data logging HTTP Node ThingSpeak update 10. Sample n8n Workflow JSON { "nodes": [ { "name": "Webhook", "type": "n8n-nodes-base.webhook" }, { "name": "AI Analysis", "type": "n8n-nodes-base.openai" }, { "name": "Telegram", "type": "n8n-nodes-base.telegram" } ] } 11. Installing n8n Using Docker docker run -it --rm \ -p 5678:5678 \ -v ~/.n8n:/home/node/.n8n \ n8nio/n8n Open: http://localhost:5678 12. Telegram Bot Setup Step 1 — Open Telegram Search: Telegram Step 2 — Create Bot Search: @BotFather Commands: /newbot Save: Bot Token Step 3 — Get Chat ID Open: https://api.telegram.org/bot/getUpdates 13. Telegram Voice Notification Method Use: Google Text-to-Speech ElevenLabs API gTTS Python module Python Voice Generator Example from gtts import gTTS text = "Warning. Gas leakage detected in factory unit." tts = gTTS(text=text, lang='en') tts.save("alert.mp3") Send MP3 through Telegram node. 14. Google Sheets Integration Step-by-Step Create Sheet Columns: Time Temp Humidity Gas Current Enable API Open: Google Cloud Console Enable: Google Sheets API Connect in n8n Use: Google OAuth credentials 15. ThingSpeak Cloud Dashboard Setup Open: ThingSpeak Create Channel Fields: Temperature Humidity Gas Current Vibration Get API Key Copy: Write API Key ESP32 Upload URL String server = "http://api.thingspeak.com/update?api_key=YOUR_KEY"; 16. AI Power Consumption Prediction Logic AI Objective Predict: Overload Abnormal current Energy waste Equipment failure Basic AI Formula Use moving average: P avg ​ = n P 1 ​ +P 2 ​ +P 3 ​ +⋯+P n ​ ​ If: Current > Threshold Then: Send alert Turn OFF relay Advanced AI Options You can use: TensorFlow Lite Edge Impulse TinyML OpenAI API 17. Voice Command Automation Supported Commands Voice Command Action Turn ON Motor Relay ON Turn OFF Motor Relay OFF Emergency Stop Shutdown Check Temperature Send sensor value Voice Recognition Methods Option 1 Telegram voice messages → n8n → AI → ESP32 Option 2 Web dashboard microphone input Option 3 Google Assistant integration 18. AI Agent Logic Agent Decisions Condition Action High Temperature Cooling ON Gas Leakage Alarm + Relay OFF High Current Shutdown Vibration Detected Maintenance Alert 19. Cloud Dashboard Features Dashboard Includes ✅ Live sensor graphs ✅ Device status ✅ AI predictions ✅ Alert logs ✅ Power analytics ✅ Historical trends 20. Future Enhancements Upgrade Ideas AI Improvements Predictive maintenance Failure forecasting ML anomaly detection Hardware Improvements Industrial PLC integration GSM backup Solar power Software Improvements Mobile app Voice assistant Multi-user control 21. Deployment Guide Industrial Deployment Steps Step 1 Assemble PCB safely. Step 2 Use isolated relay modules. Step 3 Add fuse protection. Step 4 Use industrial-grade power supply. Step 5 Deploy cloud server. Step 6 Enable HTTPS security. Step 7 Test emergency shutdown. 22. Security Recommendations Important ✅ Use HTTPS webhooks ✅ Secure API keys ✅ Use firewall rules ✅ Enable authentication ✅ Encrypt cloud communication 23. Testing Procedure Test Cases Test Expected Result Gas leakage Relay OFF High current Alert sent Voice command Device responds WiFi disconnected Auto reconnect High temperature Cooling activated 24. Real Industrial Applications Use Cases Smart factories Chemical plants Motor monitoring Energy management Boiler automation Smart agriculture Warehouse automation 25. Final Output of the System Your completed system will provide: ✅ AI-powered industrial automation ✅ Cloud-connected ESP32 monitoring ✅ Voice-controlled operations ✅ Telegram voice emergency alerts ✅ Real-time IoT dashboard ✅ Google Sheets analytics logging ✅ Intelligent predictive maintenance ✅ Remote industrial management 26. Recommended Software Stack Software Purpose Arduino IDE ESP32 programming n8n Automation Telegram Notifications ThingSpeak Cloud dashboard Google Sheets Data storage OpenAI API AI agent Docker n8n deployment 27. Recommended Project Folder Structure Industrial_AI_IOT/ │ ├── ESP32_Code/ ├── n8n_Workflow/ ├── Dashboard/ ├── AI_Model/ ├── Documentation/ ├── Telegram_Bot/ └── GoogleSheets/ 28. Conclusion This project is a complete Industry 4.0 automation solution combining: Embedded systems Artificial intelligence IoT cloud computing Automation workflows Voice communication Predictive analytics It is suitable for: Final year projects Industrial prototypes Smart factory research IoT product development AI automation systems