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Traditional safety mechanisms suffer from response lags, heavy reliance on manual smartphone operation, and delayed emergency alerts with inaccurate GPS coordinates. To address these critical shortcomings, this project introduces a compact, cost-effective, and intelligent ESP32-powered safety device designed for rapid distress signaling without requiring manual smartphone input. The system integrates a motion sensor and a microphone to automatically detect dangers—categorized as "Fall Detected" or "Loud Noise"—via a discrete double-shake gesture or a "HELP" voice command. Upon triggering, an onboard GPS module captures real-time geographical coordinates, while the ESP32-CAM captures visual evidence of the surroundings. These critical insights, alongside a direct Google Maps location link, are dispatched to predefined emergency contacts via Telegram in a persistent loop, while live data is streamed to a ThingSpeak IoT dashboard for centralized monitoring. A secure physical push-button switch allows the user to either manually deactivate the persistent loop or immediately silence the buzzer and broadcast an "I am safe" message, effectively minimizing false alarms and drastically reducing emergency response times.