Cloud-Based Flight Path Processing for Mobile Launch Monitor Analytics
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing sports performance tracking devices, such as launch monitors and golf simulators, lack comprehensive data analysis, personalized feedback, and are limited by high cost, bulkiness, and inflexibility, failing to provide mobile, cost-effective solutions that integrate advanced features like shot-specific data overlays and adaptive recommendations.
Innovation Solution
A system architecture that transforms a standard mobile device into a versatile launch monitor and simulator, leveraging machine learning and AI to capture, process, and deliver real-time data analytics, including video editing and personalized improvement suggestions, while overcoming device limitations through efficient back-end processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional launch monitors and golf simulators are used, then measurement precision and data analysis capability are improved, but device complexity, cost, and portability deteriorate
Solution Approach 1:
The patent introduces a cloud-based processing system as an intermediary between the mobile device camera and the final analysis output. The mobile device captures video and transmits it to the cloud, where sophisticated algorithms process the data to generate shot metrics, trajectory analysis, and performance feedback. This mediator approach allows the mobile device to remain simple while achieving launch monitor-level precision through remote computational power.
Solution Approach 2:
The patent replaces complex mechanical optical systems with computational methods. Instead of using expensive optical sensors and physical launch monitor hardware, the system uses smartphone cameras to capture video and applies image processing algorithms, computer vision techniques, and machine learning models to extract measurement data. This substitution eliminates the need for specialized hardware while maintaining measurement capabilities.
2Adaptability or versatility
If comprehensive data analysis and personalized feedback features are added, then functionality and user experience are improved, but device complexity and cost increase
Solution Approach 1:
The patent implements a universal processing platform that handles multiple analysis functions through a single integrated system. The cloud-based architecture provides multi-functionality including shot metric extraction, trajectory modeling, swing analysis, cumulative statistics tracking, video editing, and personalized feedback generation. This universal approach allows the system to offer comprehensive features without requiring separate specialized systems for each function.
Solution Approach 2:
The system incorporates feedback mechanisms where processed shot data and generated insights are transmitted back to the user's mobile device. The platform analyzes performance data, compares it against user goals and historical data, and provides personalized recommendations for improvement. This feedback loop enables adaptive functionality that learns from user interactions and improves over time, enhancing user experience without proportionally increasing system complexity.
3Measurement precision
If mobile device camera quality limitations are addressed, then measurement accuracy is improved, but processing time and computational requirements increase
Solution Approach 1:
The patent segments the processing workflow into distinct stages: video capture on mobile device, video transmission to cloud, automated object detection and tracking, metric calculation, and results delivery. By dividing the complex processing into sequential segments handled by different systems (mobile device for capture, cloud for analysis), the system optimizes both accuracy and processing time. Each segment can be optimized independently, with the cloud handling computationally intensive tasks while the mobile device focuses on capture and preliminary processing.
Data Source
AI summary
A system includes a platform configured to receive a video recording of a flight path of an object and initiate back-end processing of the video recording. The back-end processing may include data modeling, object detection operations, normalizing operations, adjusting normalize data based on meta_camera specifications to compensate for limitations of the user device used to create the video recording, and applying mathematical techniques to the adjusted data to derive metrics relating to the flight path of the object and to generate an enhanced video clip of the flight path. In an embodiment, the back-end processing may further include generating a trace line of the flight path of the object, adding the trace line to the enhanced video clip, transmitting the enhanced video clip and the metrics to the user device, and storing the enhanced video clip and the metrics in back-end storage.