Drowning Detection System for Swimming Pools

Pool safety systems operate in regulated environments. Compliance is not optional: it is part of the safety infrastructure. International standards define the technical and operational requirements for drowning prevention in swimming pools and for the governance of safety-critical systems.

ISO 20380 and DIN EN ISO 20380 formalize the concept of drowning as a process and establish expectations for detection, response, and supervision. DGfDB (R) 94.15 provides guidance for pool safety operations in regulated contexts. Privacy and data protection obligations are enforced under GDPR (EU 2016/679), the Data Protection Act 2018 (UK), and the Australian Privacy Principles (APP). The EU AI Act introduces a risk-based approach that requires transparency, governance, and human oversight in AI-based pool safety systems.

We are fully compliant with the General Data Protection Regulation (EU) 2016/679 (DIN EN), the Data Protection Act 2018 (UK), the Australian Privacy Principles (APP), ISO 20380, and DGfDB (R) 94.15 standards.

Compliance matters because pool safety standards and privacy laws directly affect how monitoring systems are deployed, how risk decisions are documented, and how operators demonstrate due diligence to authorities, insurers, and auditors.

For high‑intent compliance searches, this is the core requirement: a drowning detection system must be defensible, explainable, and aligned with formal standards, not just operationally effective.

Aqutron applies deterministic logic to drowning risk detection. The system evaluates physical inconsistencies between what should be visible above the water and what actually appears. This produces explainable decision paths that can be reviewed and documented.

Processing occurs at the edge. Risk assessment is performed locally, reducing latency and avoiding transmission of identifiable video streams. The system is designed for GDPR compliant pool monitoring and aligns with AI Act principles for transparency and human oversight.

The approach is non-invasive: no underwater sensors, no wearable devices, no biometric identification, and no surveillance purpose. The system supports lifeguards and operators, it does not replace human supervision.

A drowning detection system is a function of a broader pool safety system. It works alongside preventive safety measures, operational governance, and staff procedures. The goal is to create traceable, structured decision support that improves response quality without removing human responsibility.

This integration supports documentation and incident analysis. Each risk state can be logged, reviewed, and aligned with internal protocols and regulatory expectations. It also creates consistent governance across public pools, aquatic centers, and hospitality environments.

In practice, this means traceable decisions, structured escalation, and a clearer chain of accountability. A compliant pool safety system must support audits and operational reviews without relying on intrusive monitoring.

If you are evaluating drowning detection systems, consider how they connect to the broader safety strategy, not just how they trigger alerts. That is where compliance and operational resilience are achieved.

Pool safety systems must respect privacy and ethical constraints. Aqutron is designed with privacy by design principles, avoiding biometric identification and minimizing personal data processing.

The system aligns with GDPR compliance, supports data minimization, and enables auditability. It also reflects the EU AI Act risk-based approach for AI Act compliance safety systems, emphasizing transparency and human-in-the-loop decision support.

GDPR compliant pool monitoring requires clear purpose limitation and strict controls on data access. In safety‑critical environments, this is as important as detection performance, because it determines whether a system can be used in regulated settings.

Drowning detection supports lifeguards and operators by providing early risk indicators and clear context. It does not replace human supervision. Governance remains human, supported by deterministic, explainable decision paths.