According to the World Health Organization (WHO), drowning is the 3rd leading cause of unintentional injury death worldwide.
The USA Swimming Foundation reported that at least 110 children under 15 fatally drowned in pools or spas during the swim season months of June – August 2021, constituting a 30% increase from the 2020 swim season. The Royal Lifesaving Society cites swimming pools as the leading location for drowning deaths among young children in Australia, accounting for 52% of all drowning deaths. Swimming pool drownings have spiked across the EU, as well.
Clearly, preventing swimming pool drownings is a global problem requiring new solutions. We must shift from detection to prevention—to respond quickly before a drowning event unfolds.
Current Drowning Detection is Inherently Flawed
Drowning happens quickly and quietly. It doesn’t look like what most people expect. The early signs of distress are difficult to identify and easy to miss. And this is the danger.
A lifeguard or nearby swimmer may notice something, but uncertainty can lead them to wait for confirmation. As too many tragedies reveal, relying on human sight and comprehension capabilities alone hinders adequate responses.
A detection-focused strategy will not help us reach our mission of eliminating swimming pool drownings.
Overhead Cameras
Security cameras have become more prevalent throughout the swimming pool industry. These cameras primarily serve a security function, and perhaps as a tool for managers to review pool usage. However, standard CCTV cameras are not used for drowning prevention, nor are they capable of serving in such a capacity. They have significant limitations, chief among them being that they cannot see through water disturbances.
Without image-correction capability, CCTV cameras cannot prevent swimming pool drownings.
Lifeguards
Lifeguards have served as first responders to swimmers in distress for decades. However, they can’t see underwater and must juggle many tasks simultaneously, including maintaining order in the pool.
Lynxight delivers cutting-edge technology that empowers lifeguards to do their job successfully. Furthermore, it’s analytics capabilities enable pool managers to make the most efficient use of their staff and other resources, a critical advantage today, as the world experiences a lifeguard labor shortage.
Lynxight Aquatic Safety & Analytics Service
The Lynxight Aquatic Safety and Analytics Service is a new way to manage safety risks and put emphasis on prevention over detection. By utilizing the power of artificial intelligence and machine learning we’re able to overcome the inherent deficiencies in today’s response to swimming pool safety.
Artificial Intelligence (AI)
AI technology transforms standard CCTV cameras into smart cameras. Our novel software digitizes and analyzes the images captured by the CCTV cameras, effectively seeing through the water and allowing the system to track swimmers doing everything from diving to splashing around. Surface water disturbances, such as waves, ripples and glare no longer pose a problem.
Machine Learning
Machine learning is an AI application that enables a system to learn and improve itself without reprogramming. Thousands of bits of data, such as swimmer behavior profiling, distress situations and drownings collected from pools worldwide are amassed to create the special algorithms used by our drowning prevention tool.
Artificial technology and machine learning combine to quickly identify instinctive drowning response behavior. Once this happens, an alert is sent to the lifeguard, who can immediately take appropriate action to save a swimmer in distress.
Prevention Over Detection
Lynxight offers a groundbreaking solution to improve safety in any swimming pool environment. By harnessing the power of artificial intelligence and machine learning we shift from detection to prevention.
As we see from the statistics, it’s imperative that we shift our response from drowning detection to drowning prevention. The Lynxight Aquatics Safety and Analytics Service utilizes the capabilities of artificial technology and machine learning to prevent swimming pool drownings.
- Standard CCTV cameras are converted into smart cameras that utilize AI image-correction software to clearly see everything that is happening in the swimming pool.
- Machine learning algorithms recognize the predictable behaviors that are present when a swimmer is drowning.
- Algorithms and AI image correction combine to create a one-of-a-kind technology to prevent swimming pool drownings.