AI-Based Women Safety Device with Voice Recognition and Emergency Alerts

AI-Based Women Safety Device with Voice Recognition & Emergency Alerts ESP32 + Agentic IoT + n8n Automation + Telegram Voice Alerts + Google Sheets + ThingSpeak + AI Prediction

AI-Based Women Safety Device with Voice Recognition & Emergency Alerts ESP32 + Agentic IoT + n8n Automation + Telegram Voice Alerts + Google Sheets + ThingSpeak + AI Prediction This project is a smart women safety wearable/device built using: ESP32 Voice trigger / panic detection GPS location tracking AI-powered risk & battery prediction Emergency automation using: n8n Telegram Bot API Google Sheets ThingSpeak IoT Cloud The system can: Detect emergency situations Trigger SOS alerts Send GPS coordinates Generate voice alerts on Telegram Store incident history in Google Sheets Display live data in ThingSpeak dashboard Predict battery usage using AI logic Enable future AI-agent based decision making 1. PROJECT OVERVIEW Objective Develop an intelligent women safety system capable of: Emergency detection Voice-triggered activation Real-time cloud monitoring Automated alerting AI-based predictive analytics 2. SYSTEM ARCHITECTURE Overall Workflow User in danger ↓ Voice trigger / Panic button pressed ↓ ESP32 collects: - GPS location - Device status - Audio trigger - Battery level ↓ ESP32 sends data to: - n8n webhook - ThingSpeak cloud ↓ n8n automation: - Sends Telegram alert - Converts text to voice - Logs to Google Sheets - Triggers AI workflow ↓ Emergency contacts receive: - Message - Live location - Voice alert 3. COMPONENTS LIST Component Quantity Purpose ESP32 Dev Board 1 Main controller GPS Module NEO-6M 1 Location tracking Microphone Sensor (MAX9814 / KY-038) 1 Voice detection Push Button 1 Panic switch Buzzer 1 Alarm indication OLED Display (Optional) 1 Status display Li-ion Battery 1 Portable power TP4056 Charging Module 1 Battery charging SIM800L (Optional) 1 GSM backup alerts Jumper Wires — Connections Breadboard / PCB — Prototype 4. CIRCUIT SCHEMATIC CONNECTIONS ESP32 Pin Connections Module ESP32 Pin GPS TX GPIO16 (RX2) GPS RX GPIO17 (TX2) Panic Button GPIO4 Buzzer GPIO5 Microphone OUT GPIO34 Battery Voltage GPIO35 OLED SDA GPIO21 OLED SCL GPIO22 5. CIRCUIT WORKING Step-by-Step 1. ESP32 Initialization WiFi connection established Sensors initialized Telegram/n8n endpoints loaded 2. Monitoring State ESP32 continuously checks: Panic button Voice trigger Battery level 3. Emergency Trigger If: Panic button pressed OR Voice keyword detected ("HELP", "SAVE ME") then: GPS fetched Alarm activated Cloud notification sent 4. n8n Workflow Executes n8n: Receives webhook data Sends Telegram alert Generates voice message Logs incident Stores AI analytics 6. FLOWCHART START ↓ Initialize ESP32 ↓ Connect WiFi ↓ Read Sensors ↓ Emergency Detected? ┌─────────────┐ │ NO │ │ Continue │ └─────┬───────┘ ↓ YES ↓ Get GPS Location ↓ Send Data to n8n ↓ n8n Sends: - Telegram Alert - Voice Message - Google Sheets Log ↓ Update ThingSpeak ↓ Activate Buzzer ↓ END 7. ESP32 SOURCE CODE Required Libraries Install from Arduino IDE: WiFi.h HTTPClient.h TinyGPS++ ArduinoJson ESP32 Arduino Code #include #include const char* ssid = "YOUR_WIFI"; const char* password = "YOUR_PASSWORD"; String webhook = "YOUR_N8N_WEBHOOK"; #define BUTTON_PIN 4 #define BUZZER_PIN 5 void setup() { Serial.begin(115200); pinMode(BUTTON_PIN, INPUT_PULLUP); pinMode(BUZZER_PIN, OUTPUT); WiFi.begin(ssid, password); while(WiFi.status() != WL_CONNECTED){ delay(500); Serial.print("."); } Serial.println("WiFi Connected"); } void loop() { if(digitalRead(BUTTON_PIN)==LOW){ digitalWrite(BUZZER_PIN, HIGH); if(WiFi.status()==WL_CONNECTED){ HTTPClient http; http.begin(webhook); http.addHeader("Content-Type","application/json"); String jsonData = R"({ "status":"EMERGENCY", "latitude":"17.3850", "longitude":"78.4867", "battery":"78" })"; int response = http.POST(jsonData); Serial.println(response); http.end(); } delay(5000); digitalWrite(BUZZER_PIN, LOW); } } 8. n8n AUTOMATION WORKFLOW n8n Workflow Overview Webhook Trigger ↓ Parse JSON ↓ Telegram Message ↓ Text-to-Speech ↓ Telegram Voice Alert ↓ Google Sheets Entry ↓ ThingSpeak Update 9. n8n WORKFLOW JSON { "nodes": [ { "name": "Webhook", "type": "n8n-nodes-base.webhook" }, { "name": "Telegram", "type": "n8n-nodes-base.telegram" }, { "name": "Google Sheets", "type": "n8n-nodes-base.googleSheets" } ] } 10. TELEGRAM BOT SETUP Step 1: Open Telegram Search: Telegram Step 2: Open BotFather Search: BotFather Step 3: Create Bot Command: /newbot Provide: Bot Name Username You receive: BOT TOKEN Save this token. Step 4: Get Chat ID Open: https://api.telegram.org/botTOKEN/getUpdates Send message to bot. Find: chat:{ "id":123456 } 11. TELEGRAM ALERT MESSAGE FORMAT Text Alert 🚨 WOMEN SAFETY ALERT 🚨 Emergency Detected! Location: https://maps.google.com/?q=LAT,LON Battery: 78% Immediate assistance required. 12. TELEGRAM VOICE ALERT AUTOMATION Workflow Emergency Text ↓ Google TTS API ↓ MP3 Voice ↓ Telegram Voice Message Voice Message Example Emergency detected. Please help immediately. Location has been shared. 13. GOOGLE SHEETS INTEGRATION Create Google Sheet Example columns: Timestamp Latitude Longitude Battery Status Connect Google Sheets to n8n Steps Create Google Cloud Project Enable Google Sheets API Create OAuth Credentials Add credentials in n8n Select spreadsheet 14. THINGSPEAK CLOUD DASHBOARD SETUP Create Account Open: ThingSpeak Dashboard Create Channel Fields: Emergency Status Battery % Latitude Longitude API Write URL https://api.thingspeak.com/update?api_key=KEY 15. AI POWER CONSUMPTION PREDICTION Objective Predict: Remaining battery life Device active duration Alert frequency Parameters Used Parameter Description WiFi Usage Current draw GPS Usage Tracking load Alerts Sent Communication usage Battery Voltage Power status AI Logic Simple prediction: Battery Remaining = Current Battery - (Average Hourly Consumption × Time) Future AI Enhancement Use: TinyML TensorFlow Lite Edge AI for: Behavior prediction Threat pattern detection Voice emotion analysis 16. VOICE RECOGNITION SYSTEM Basic Method ESP32 microphone listens for: "HELP" "SAVE ME" "EMERGENCY" Advanced AI Method Use: Edge Impulse TinyML Keyword Spotting Platforms: Edge Impulse TensorFlow Lite for Microcontrollers 17. THINGSPEAK DATA VISUALIZATION Dashboard Charts: Battery graph Emergency count GPS mapping Alert timeline 18. AI AGENTIC AUTOMATION IDEAS AI Agent Can: Auto-call nearest police Detect repeated danger zones Analyze user movement Predict unsafe areas 19. SECURITY FEATURES Feature Description HTTPS Secure communication API Tokens Authentication GPS Encryption Privacy Backup Alerts GSM redundancy 20. FUTURE ENHANCEMENTS Hardware Smartwatch integration Hidden wearable design Solar charging AI Emotion recognition Violence sound detection Real-time AI assistant Cloud Firebase integration AWS IoT Real-time dashboards 21. DEPLOYMENT GUIDE Prototype Stage Breadboard testing Serial monitor debugging PCB Design Use: KiCad EasyEDA Mobile Integration Android app Flutter dashboard 22. TESTING PROCEDURE Test Cases Test Expected Result Panic button Telegram alert Voice trigger Emergency activated Internet lost GSM backup Low battery Warning alert 23. PROJECT FOLDER STRUCTURE WomenSafetyAI/ │ ├── ESP32_Code/ ├── n8n_Workflow/ ├── TelegramBot/ ├── GoogleSheets/ ├── ThingSpeak/ ├── AI_Model/ ├── Documentation/ └── CircuitDiagram/ 24. COMPLETE DATA FLOW ESP32 ↓ WiFi ↓ n8n Webhook ↓ Telegram + Google Sheets + ThingSpeak ↓ Emergency Contacts 25. ADVANCED FEATURES YOU CAN ADD AI Features Face recognition Danger sound classification Automatic distress detection IoT Features Live GPS tracking Geofencing Cloud analytics Smart Automation Auto siren activation Nearby hospital notification Emergency call automation 26. REAL-WORLD APPLICATIONS Women safety wearable Child safety tracking Elderly emergency system Smart security device 27. FINAL OUTPUT OF SYSTEM When emergency occurs: ✅ Buzzer activates ✅ GPS captured ✅ Telegram text sent ✅ Voice alert sent ✅ Google Sheets updated ✅ ThingSpeak dashboard updated ✅ AI prediction generated 28. RECOMMENDED SOFTWARE TOOLS Tool Purpose Arduino IDE ESP32 programming n8n Automation Workflow automation ThingSpeak IoT cloud Google Cloud Console API management EasyEDA PCB design 29. ESTIMATED PROJECT COST Item Approx Cost Total:8000/- This project combines: AI IoT Cloud Automation Edge Computing Real-Time Emergency Response to create a powerful intelligent women safety system using: ESP32 n8n Telegram ThingSpeak Google Sheets This can be developed into: Wearable safety band Smart pendant Smart mobile assistant AI-enabled emergency ecosystem