A wearable detection system that uses sensor data to detect medical emergencies (such as falls) and automatically alerts to a companion application. Finding the nearest 'Medic' to aid the user for a chance to prolong life expectancy while awaiting professional help, which then generates AI-powered incident reports.

This project combines embedded hardware, device communication, and AI-based report generation to detect fall incidents and produce structured incident reports in real time. The system is designed for applications such as elderly care, workplace safety, and personal health monitoring.

• Fall detection using accelerometer data
• ESP32-based wireless communication
• Push-button confirmation incident trigger
• Automatic AI-generated incident reports
• Cloud integration for data storage and retrieval

• Sensor Node (Arduino-based)
  • Detects falls using an accelerometer
  • Sends events via serial communication
• ESP32 Gateway
  • Receives fall and button events
  • Handles wireless transmission
• Mobile / Cloud Application
  • Generates incident reports using AI
  • Stores reports in Firebase

• ESP32
• MMA7660 Accelerometer
• RGB LCD Backlight
• Push Button

• Arduino IDE
• I2C, UART

• Swift (iOS – Xcode)
• Firebase
• Gemini AI API

1. The accelerometer continuously monitors motion along the Z-axis.
2. A sudden acceleration drop exceeding a defined threshold triggers a fall event.
3. A manual button press can confirm an incident is occuring and needs attention.
4. Events are transmitted to the ESP32 via serial communication.
5. The ESP32 forwards incident data to FireBase.
6. The application uses AI to generate a structured incident report and stores it in Firebase.

1. Open the Arduino code in Arduino IDE
2. Connect the hardware components
3. Upload the sensor firmware
4. Upload the ESP32 firmware

1. Clone the repository
2. Open the project in Xcode
3. Configure Firebase
4. Add Gemini API credentials
5. Build and run on an iOS device or simulator

• Adjust fall detection thresholds in the Arduino code
• Configure Firebase project settings