Drowning prevention in commercial pools: harnessing AI technology for safer swimming

What does drowning prevention in commercial pools mean today?

Commercial pools faceunique safety challengesthat imply distinct drowning prevention strategies must be applied.

On the one hand, unlike residential pools, they accommodate high swimmer density, including diverse age groups, and frequent movement that can obscure visibility.

On the other hand, while lifeguards are trained professionals, they are human —and human vigilance has its limits. Fatigue, distraction, and limited visibility can hinder even the most attentive safety personnel.

As such, drowning prevention in commercial pools requires a focus on implementing all supervision opportunities at hand.

Today, this includes the possibility to support human supervision with technology.

A comprehensive safety strategy that involves intelligent surveillance systems that enhance human oversight through real-time monitoring and predictive alerts.

Enter smart safety systems: the current technologies enabling better drowning prevention

Recent advancements have introduced AI-powered drowning detection systems that operate alongside lifeguards, taking drowning prevention to the next level.

The case of Lynxight is worth mentioning as a company that specializes in AI and computer vision to enhance pool safety. A technology that showcases how machine learning and real-time image processing can be leveraged to drastically reduce response times in life-threatening situations.

How drowning prevention technology works

This system devised by Lynxight uses existing overhead cameras or dedicated vision sensors to continuously monitor swimmer activity.

Through AI algorithms trained to detect signs of distress, the system is then in charge of identifying anomalies, such as prolonged immobility, unusual motion patterns, or submersion beyond a safe duration.

If such scenarios occur, the system sends instant alerts to lifeguards or facility operators through smartwatch and/or the reception screen, allowing them to intervene quickly —often before a critical situation escalates. A system that is especially beneficial during busy hours or when visibility is impaired by crowding, splashing, or poor lighting conditions.

Key benefits of AI-based drowning prevention systems

1. Faster response times

In a drowning emergency, every second counts: studies show that brain damage can occur within minutes of submersion, while survival chances drop sharply with every passing moment.

In these scenarios, AI systems are valuable for their capacity to detect signs of trouble within seconds, significantly reducing the window between incident and rescue.

2. Augmented lifeguard capabilities

Rather than replacing lifeguards, these systems serve as a digital assistant—alerting staff to high-risk swimmers or escalating incidents. As such, they act as technological support, helping lifeguards focus their attention effectively and respond with greater precision.

3. Data-driven safety insights

Modern systems log every alert, event, and pool activity in a control panel. This serves as valuable swimming prevention intelligence, as the data collected allows facility managers to analyze pool uses, safety performance and patterns.

This, in turn, can inform a number of processes that, ultimately, generate better drowning prevention protocols, including:

• Training and performance reviews
• Understanding peak risk periods
• Preventative safety planning interventions

For instance, analyzing video footage from lifeguards’ responses to drowning incidents could provide feedback in order to improve vigilance. Additionally, the system could help design smarter safety infrastructure by analyzing which locations have most commonly led to incidents.

4. Non-invasive and privacy-conscious

Unlike wearable-based drowning alerts that require swimmers to use devices, AI-powered vision systems are non-intrusive. As such, they are built to protect privacy by processing video data without storing personally identifiable visuals, complying with strict data regulations like GDPR.

5. Scalability and retrofit potential

Systems like those by Lynxight described above in this article are designed to easily integrate with existing pool infrastructure. This feature means the system can adapt to and upgrade facilities of all sizes, from community centers to Olympic-size pools.

AI + Human safety: a new model for drowning prevention

The adoption of innovative drowning prevention systems is no longer a futuristic concept. Today, connected pool technology is emerging as a response to the growing demand for smarter and safer public aquatic facilities.

As commercial pool operators seek to reduce liability, enhance patron safety, and comply with evolving safety standards, technologies are promoting drowning prevention processes that are optimized and more effective.

In fact, these systems not only save lives, but also offer operational efficiencies for pool owners, including:

• Reduced insurance premiums
• Fewer false alarms
• Enhanced public trust and facility reputation

In this context, AI drowning prevention systems are not emerging as replacements for trained lifeguards. Instead, they add a layered approach to safety, where human oversight is reinforced with machine intelligence to enhance drowning prevention protocols.

A combined strategy —known as the “Human + AI” safety model— that has been shown to significantly enhance overall incident prevention and response outcomes.

As such, at Fluidra, we’ve incorporated advanced drowning prevention equipment to our Safety Elements catalogue, helping pool professionals ensure their installations put bathers’ safety at the center.

FAQs about drowning prevention

What is the definition of drowning prevention?

Drowning prevention refers to a collection of strategies whose goal is reducing the risk of drowning incidents. As such, it involves taking a proactive approach that seeks to stop risky events before they happen, instead of merely reacting to them.

This approach involves a series of measures in different areas and with distinct goals, from education and awareness to the implementation of specialized human and technological supervision.

How can we prevent drowning?

Drowning prevention must be constructed from a layered perspective that includes proactive interventions to both reduce the risk of drowning incidents while also being able to promptly respond to them when needed.

As such, preventing drowning often involves the following:

• Providing educational and awareness initiatives around drowning risks, as well as water skills development including swimming and floating.
• Interventions in aquatic facilities to make them safer. While these interventions should adapt to each pool’s needs and actual use, fencing or adding barriers and safe doors to swimming pools is often advisable.
• Ensuring close and constant supervision in pools is non-negotiable to proactively avoid drowning incidents. As seen above in this article, human lifeguards can be aided by supervision technologies in order to enhance their capacities and improve response outcomes. In the case of children, an adult should be designated to supervise swimming even if lifeguards are present.
• For commercial pool operators, drowning prevention also involves having emergency response protocols in place that ensure rapid response to incidents.

What is the most effective drowning prevention strategy?

As discussed above, drowning prevention consists of a number of layers that go from education to emergency response protocols and that, altogether, are capable of minimizing risks related to drowning.

However, if one single drowning prevention strategy should be highlighted, it should be that of supervision, meaning the continuous attentive monitoring of individuals in or near water, allowing immediate intervention if signs of distress arise.
Today, and as seen across this article, human supervision is being supplemented by AI and monitoring technologies, which support human lifeguards in early detection with the aim of minimizing incidents.