Kyle Chuang¹, Jonathan Sahagun²,¹USA, ²California State Polytechnic University, USA

Drowning represents a significant global public health crisis, with approximately 300,000 deaths occurring annually worldwide, disproportionately affecting children under the age of five [1]. Despite the presence of supervising adults in 80% of child drowning incidents, the silent and rapid nature of drowning events often prevents timely intervention. This paper presents SafeSwim, an intelligent wearable drowning detection and alert system that integrates accelerometer-based motion detection, underwater acoustic signaling, and mobile application technology to provide real-time alerts to caregivers. The system comprises three primary components: a wearable device utilizing an Adafruit RP2040 Prop-Maker Feather with a LIS3DH accelerometer that detects abnormal motion patterns and generates low-frequency acoustic signals, a Raspberry Pi-based receiver equipped with an Aquarian Audio H2d hydrophone that processes underwater acoustic signals using Fast Fourier Transform analysis, and a Flutter-based mobile application connected to Firebase for device management and alert delivery. Experimental evaluation demonstrated reliable detection of simulated drowning events with minimal false positives. The system addresses limitations of existing approaches by providing non-intrusive monitoring that does not impede swimming ability while ensuring rapid alert transmission to nearby adults.

Drowning, Protection, IoT, Hydrophone, Underwater Acoustics