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Top 4 – Team 22

TinyML-Powered Edge AI Hand Band for Sudden Fall Detection

TinyML Fall Guard is a smart hand band designed for safety monitoring. It continuously tracks hand movement using the MPU6050 motion sensor. The collected data is processed by an ESP32 controller running a TinyML model.

Inside the build

🏅 Top 4 – Team 22

Project: TinyML-Powered Edge AI Hand Band for Sudden Fall Detection

TEAM MEMBERS:

  • Shama AJ
  • Sheethal R Bangera
  • Srujan
  • Sushanth

Creativity: TinyML Fall Guard is a smart hand band designed for safety monitoring. It continuously tracks hand movement using the MPU6050 motion sensor. The collected data is processed by an ESP32 controller running a TinyML model.

When sudden abnormal movement is detected, the system identifies it as a possible fall. Instead of sending an alert immediately, the system waits for a short period to check whether the person resumes normal movement. If normal movement is detected, the system considers the user safe and turns on the green LED. If no recovery movement is observed, the system enters danger mode. In danger mode, the red LED and buzzer are activated. The T5848 microphone is turned on to further confirm whether the user is in distress. After confirmation, an emergency alert is sent through Wi-Fi. A push button is also provided so the user can manually request help at any time.

Presentation & Documentation: Download file

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