Virtual Booth

Accidental falls present a severe safety hazard for elderly individuals and vulnerable people living alone, where delayed medical responses can lead to critical complications. This project introduces FallSense AI, an AI-powered fall detection and IoT emergency notification system designed for real-time indoor safety monitoring. Built around an ESP32 microcontroller, the system integrates a HuskyLens AI vision sensor to continuously monitor designated spaces and recognize abnormal postures associated with human falls.

Upon detecting a fall event, the HuskyLens sends signals to the ESP32 to initiate a dual-layer emergency protocol. Locally, the system activates a visual LED indicator and an audible piezo buzzer to sound an immediate alert. Simultaneously, leveraging Wi-Fi connectivity and the Telegram API, the ESP32 dispatches instant notifications—including the fall location and exact timestamp—directly to caregivers' smartphones anywhere in the world.

Programmed using C++/Arduino IDE, FallSense AI combines low power consumption, affordability, and ease of installation into a non-invasive monitoring solution. By automating threat detection and emergency dispatching, this prototype bridges computer vision with IoT connectivity, offering an efficient, reliable framework for senior care, assisted living facilities, and smart home monitoring.