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LAIF: Leveraging AI to Prevent Drownings at Sea

Overview

LAIF is an advanced predictive aquatic surveillance system developed through collaboration between CIMNE and Pro-activa Serveis Aquàtics, with support from the Catalan Business Competitiveness Agency (ACCIÓ). This innovative technology combines Computer Vision and Artificial Intelligence (AI) to automatically detect behaviours in aquatic environments that are compatible with drowning situations.

The system continuously analyses real-time video streams from cameras positioned at beaches and pools, identifying potential drowning scenarios that might be difficult for human observers to detect. When a risky situation is identified, LAIF immediately sends alerts to control centres and lifeguard teams, enabling rapid emergency response that can save lives.

Beyond enhancing existing surveillance capabilities, LAIF represents a paradigm shift in water safety by enabling 365-day-a-year monitoring coverage, including in areas where permanent lifeguard presence is not feasible. The system is designed to complement rather than replace human lifeguards, providing an additional layer of protection that can detect subtle risk indicators such as medical complications that may not show obvious external signs.

The Castelldefels Demonstrator

The LAIF technology is currently operational in a pilot phase at Castelldefels Beach, near Barcelona. This real-world deployment serves as a proof of concept and testing ground for the technology’s capabilities in an active beach environment.

- System Configuration: Multiple cameras have been strategically positioned to monitor bathing areas, capturing comprehensive coverage of the aquatic zone. These cameras transmit live video feeds without recording, respecting privacy while maintaining security.
- Real-Time Analysis: The AI-powered computer vision algorithms continuously process the video streams, analysing swimmer behavior patterns and water conditions. The system has been trained to recognize various indicators of distress or drowning risk.
- Alert Mechanism: When the system detects a potentially dangerous situation, it automatically generates an alert that is sent to a control centre. Emergency protocols are then activated, and lifeguard teams are immediately notified to respond.

In Autumn 2025 a second pilot will be launched in a swimming pool in Barcelona, extending the technology’s application to controlled aquatic environments and validating its adaptability to different scenarios

Features

Real-Time Detection

Advanced computer vision algorithms analyse swimmer behaviour patterns in real time, identifying potential drowning situations as they develop.

AI-Powered Analysis

Machine learning models trained to recognize subtle indicators of distress that may be difficult for human observers to detect.

Automatic Alerts

Immediate notification system that sends alerts to control centres and lifeguard teams when risky situations are detected.

Privacy-Focused

Live streaming without recording capabilities, ensuring surveillance while respecting beachgoer privacy.

Low Latency Response

Minimal delay between detection and alert generation, maximizing the time available for emergency response.

Autonomous Operation

Designed for deployment with renewable energy sources, enabling sustainable monitoring in remote locations.

Multi-Environment

Adaptable to various aquatic settings including beaches, swimming pools, and other recreational water facilities.

Continuous Monitoring

Capability for 365-day operation, providing year-round water safety coverage beyond traditional lifeguard seasons.

Applications and Societal Benefits

Enhanced Lifeguard Support

Augments human surveillance capabilities by providing an additional monitoring layer that never loses focus or attention.

Drowning Prevention

Contributes to minimizing drowning incidents, avoiding high personal and social costs.

Medical Emergency Detection

Identifies subtle signs of medical complications in water, such as cardiac events or seizures, that may not show obvious drowning behaviors.

Pool Safety Enhancement

Designed for both natural and artificial bodies of water, the LAIF technology is applicable in public and private swimmingpools.

Extended Coverage Areas

Enables water safety monitoring in locations where permanent lifeguard presence is not economically viable or practical.

Off-Season Protection

Maintains surveillance during off-peak periods, allow for an optimal balance between safety and resources.

Cost-Effective Safety

Provides municipalities with a more efficient investment in public safety resources, reducing the overall efficiency.

Training Data Generation

Provides valuable private insights and data for improving lifeguard training programs and emergency response protocols.

Learn More

Project Information

Media Coverage

- ACCIÓ: Catalan Company Creates AI-Based System to Prevent Beach Drownings

Project Partners

Contact Us

Interested in learning more about LAIF or exploring how this technology can enhance water safety in your community?

Our Technology Transfer Unit is ready to discuss how LAIF can be adapted to your specific needs and help prevent drownings in your aquatic facilities.

Send us an email

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