AI-Driven Real-Time Kick Classification
Transforming Olympic Taekwondo with Sensor Fusion & AI
This paper proposes an AI-powered scoring system that integrates existing PSS sensors with additional accelerometers, gyroscopes, magnetic/RFID, and impact force sensors in a sensor fusion framework. The system classifies kicks in real-time to identify technique type, contact location, impact force, and even the part of the foot used, aiming to improve scoring fairness, reduce rule exploitation, encourage dynamic techniques, and enhance spectator understanding and excitement.
Quantifiable Impact & Performance
Leveraging advanced sensor fusion and machine learning, our AI-enhanced system delivers precise, real-time kick classification, setting new benchmarks for accuracy and operational efficiency in sports technology.
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Kick Classification Accuracy
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Max Scoring Latency
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Max Reward for Dynamic Kicks
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Projected Spectator Engagement Increase
Deep Analysis & Enterprise Applications
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98%
Accuracy in Basic Kick Classification (waist sensor, SVM)
A 2024 study by Liu et al. demonstrated remarkable accuracy in distinguishing four basic kick types using just a single waist-mounted accelerometer and an SVM classifier. Our system leverages an even richer sensor set and ensemble SVMs for even finer discrimination.
Enterprise Process Flow
Sensor Data Input
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Data Sync & Acquisition
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Event Segmentation
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Feature Extraction
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SVM Classification
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Score Determination
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Points Awarded
| Feature | Current PSS Limitations | AI-Enhanced System Benefits |
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| Technique Recognition |
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| Scoring Fairness |
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| Spectator Engagement |
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Redefining Olympic Taekwondo
The proposed AI-enhanced system aims to revitalize Olympic Taekwondo by shifting incentives and enhancing engagement.
Challenge: Prior systems fostered static gameplay and led to spectator disinterest, prompting IOC pressure for reform. Athletes optimized for low-risk, high-reward taps.
Solution: By recognizing and rewarding complex, dynamic kicks like tornado kicks (5 points) and back kicks (4 points), the system incentivizes more exciting techniques. The automated scoring enhances fairness and transparency.
Outcome: Anticipate higher scoring bouts, diverse tactical toolkits, and clearer action narratives for fans. The sport will realign with its martial art heritage of explosive, high-flying kicks.
Calculate Your Potential AI Impact
Estimate the annual operational savings and reclaimed human hours by deploying AI-driven sensor fusion in your competitive sports or activity recognition systems.
Estimated Annual Savings
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Annual Hours Reclaimed
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Implementation Roadmap & Next Steps
Our phased approach ensures a smooth integration of AI-driven sensor fusion into your operations, from pilot development to full-scale deployment and continuous optimization.
Phase 01: Pilot System Development & Data Collection
Develop prototype hardware and software modules, integrate sensors (IMUs, magnetic, impact) into athlete gear, and initiate extensive data collection for diverse kick techniques across multiple athletes. Establish baseline accuracy with initial SVM models.
Phase 02: Field Trials & Refinement
Conduct trials at smaller Taekwondo competitions, gathering feedback from athletes, coaches, and officials. Iteratively refine the AI classification models and scoring rubric based on real-world performance and user input. Explore ensemble SVMs and data augmentation to boost accuracy.
Phase 03: Full Integration & Rollout
Deploy the AI-enhanced scoring system in major competitions. Establish continuous monitoring for system performance, fairness, and spectator engagement. Implement a feedback loop for ongoing model improvements and adaptation to evolving techniques and rules.
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