Swimmer Behavior Tracking for Proactive Drowning Detection
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Solution Overview
Problem
Current drowning detection systems are reactive, lack proactive monitoring of swimmers, and have high operational burdens, leading to missed incidents and low market adoption due to their design focusing on detecting victims rather than tracking swimmer behavior and lacking redundancy.
Innovation Solution
A wireless system of potential drowning incident detectors (PDIDs) that track swimmers, providing alerts through a hub or base station when a swimmer's signals are not received, with features like mesh networking for scalable coverage, zoned alerts, and integration with smart home systems for enhanced monitoring and prevention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional drowning detection systems focus on detecting victims, then they can identify drowning incidents, but they have high operational burdens and miss many incidents due to reactive monitoring
Solution Approach 1:
The patent inverts the traditional approach by shifting from victim detection to swimmer behavior tracking. Instead of trying to detect drowning victims after they are in distress, the system monitors swimmers' behaviors and patterns to predict and prevent drowning incidents before they occur. This inversion fundamentally changes the detection paradigm from reactive to proactive, improving reliability while reducing operational burden through automated behavioral analysis.
Solution Approach 2:
The patent replaces manual lifeguard monitoring with an automated electronic system that uses sensors, machine learning algorithms, and computer vision to track and analyze swimmer behaviors. This substitution eliminates the high operational burden associated with human supervision while maintaining or improving detection accuracy through consistent, fatigue-free automated monitoring.
2Loss of time
If drowning detection systems use reactive monitoring, then they can identify incidents after they occur, but they result in missed incidents and delayed response times
Solution Approach 1:
The patent implements preliminary action by continuously monitoring swimmer behaviors and identifying at-risk patterns before drowning incidents occur. The system proactively detects abnormal behaviors such as prolonged submersion, erratic movements, or failure to respond to surface calls, and triggers alerts before the swimmer actually drowns. This preliminary detection dramatically reduces response time and improves incident detection reliability.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously receives data from sensors, analyzes swimmer behaviors, and provides real-time feedback through alerts to lifeguards. The system learns from accumulated data and improves its detection algorithms over time, creating a closed-loop system that enhances both response time and detection reliability through iterative optimization.
3Reliability
If drowning detection systems lack proactive monitoring, then they are simpler to operate, but they have high false negative rates and miss drowning incidents
Solution Approach 1:
The patent implements self-service through automated behavioral analysis and incident detection. The system independently monitors swimmers, analyzes behaviors using machine learning algorithms, identifies at-risk patterns, and triggers alerts without requiring constant human intervention or complex manual operation. This self-service capability maintains high detection accuracy while preserving ease of operation.
Solution Approach 2:
The patent utilizes parameter changes by monitoring multiple variables such as movement patterns, submersion duration, heart rate, and respiratory rates. The system dynamically adjusts detection thresholds and alert criteria based on learned behavioral patterns and environmental conditions. This multi-parameter approach enhances detection accuracy while the automated parameter adjustment keeps the system easy to operate.
4Adaptability or versatility
If drowning detection systems focus on victim detection rather than swimmer behavior tracking, then they have simpler design, but they lack redundancy and have low market adoption
Solution Approach 1:
The patent achieves universality by designing a system that performs multiple functions: it tracks swimmer positions, analyzes behaviors, predicts drowning risks, provides real-time alerts, and continuously learns from data. This multi-functional approach enhances adaptability and versatility while the integrated design keeps complexity manageable through unified architecture.
Solution Approach 2:
The patent applies segmentation by dividing the monitoring system into modular components: sensor modules for data collection, processing modules for behavioral analysis, prediction modules for risk assessment, and alert modules for notifications. This segmentation allows the system to provide comprehensive monitoring capabilities while maintaining manageable complexity through modular, independently deployable components.
Data Source
AI summary
A potential drowning incident detection system and its constituent components are disclosed. The system includes a device worn on a head of a swimmer, which includes one or more signal generating units. The signal generating units may be positioned on the device adjacent each temple of the swimmer when worn. The system further includes at least one hub configured to receive wireless signals from the signal generating units, and may further be in communication with a server. The hub and/or server may generate an alert or warning when the signals of the signal generating units are not received by the at least one sensor hub. The alert or warning may further be triggered to a wearable device provided to a responder, such as a life guard. Data collected from the swimmer-worn devices may be stored for later analysis.