Sports Sensor Data Processing via Inference Engine
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Solution Overview
Problem
Conventional sports-related sensors generate vast amounts of data that are not effectively utilized to inform game strategies, as they lack efficient processing and analysis methods to provide actionable recommendations to players.
Innovation Solution
A system and method that processes sensor data from sports equipment using an inference engine to generate recommendations, categorizing data into distinct sets based on timestamps, comparing current and historical player profiles, and dynamically providing feedback based on performance changes and equipment attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sports sensors collect comprehensive sensor data including pressure, string tension, and shot detection, then measurement precision and data completeness are improved, but data processing complexity and information overload increase
Solution Approach 1:
The patent segments sensor data into multiple distinct sets based on timestamps and data types. The processor divides comprehensive sensor data into first sensor data sets (during contact periods) and second sensor data sets (between contact periods), allowing selective processing of different data types for specific analytical purposes, thereby reducing overall processing complexity while maintaining measurement precision
Solution Approach 2:
The patent introduces an inference engine as an intermediary component between sensor data collection and analysis. This inference engine automatically generates insights and recommendations from the segmented sensor data sets, acting as a mediator that transforms raw comprehensive data into actionable intelligence without requiring complex manual processing
2Loss of information
If all sensor data is processed and analyzed, then information completeness is improved, but loss of time for generating actionable recommendations increases
Solution Approach 1:
The patent performs preliminary segmentation of sensor data into contact and non-contact period sets during data collection. By pre-organizing data into meaningful temporal segments, the system eliminates the need for complex post-processing analysis, enabling faster generation of actionable recommendations while maintaining complete information from all sensor sources
Solution Approach 2:
The patent selectively processes only the most relevant sensor data sets for specific analytical purposes. Rather than processing all sensor data uniformly, the system focuses on first sensor data sets during contact periods for shot analysis and second sensor data sets for between-shot patterns, reducing analysis time while maintaining information completeness for decision-making
3Measurement precision
If sensor data is categorized into multiple sets based on contact periods, then analytical precision is improved, but device complexity increases
Solution Approach 1:
The patent segments sensor data into distinct sets based on contact period detection. The processor identifies when the sports implement contacts the ball and creates separate data sets for contact periods versus non-contact periods, enabling precise analytical treatment of different operational phases without requiring complex manual categorization
Data Source
AI summary
Various aspects of a system and method to process sensor data are disclosed herein. In an embodiment, the method includes receipt of sensor data from one or more sensors associated with an item of sports equipment. The received sensor data is analyzed by use of an inference engine. One or more recommendations are generated based on the analyzed sensor data.