DrownNet: Infant Drowning Alert System using Deep Learning

The Infant Drowning Prevention System (IDPS) is a vital innovation aimed at combating the tragic loss of young lives due to drowning incidents. The Infant Drowning Prevention and Alert System (IDPAS) is a crucial innovation designed to prevent the tragic loss of young lives due to drowning incidents. By leveraging advanced Video Vision Transformers (VVTs), the IDPAS accurately detects potential drowning behaviors in infants and toddlers, ensuring swift alerts to caregivers for timely intervention. Its Smart Watching System, powered by sophisticated deep learning algorithms like CNNs and RNNs, continuously monitors video streams for subtle cues indicative of distress in water. Through ongoing learning from annotated examples and historical data, the IDPAS refines its ability to differentiate between safe interactions and risky situations, enabling rapid alerts via SMS, push notifications, or audible alarms upon detecting potential drowning events.Administrators can easily configure settings through a streamlined web interface, while pool managers have a dedicated dashboard for camera setups and emergency contacts. Caregivers receive instant alerts via SMS, email, or in-app notifications, empowering quick responses to risks. Data privacy and security are prioritized, to protect sensitive information, ensuring compliance with regulations while significantly enhancing infant safety.The proposed DrownNet system within the IDPAS offers an impressive 96% accuracy compared to other models in the literature, highlighting its quality and completeness. The integration of high accuracy, real-time monitoring, and user-friendly interface makes the IDPAS an essential tool for drowning prevention, providing comprehensive coverage and reliable alerts to prevent potential drowning incidents effectively.