Custom Outsole Pattern Generation via Sensor Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for customizing sports apparel, such as shoes, do not effectively account for long-term variations in performance characteristics and environmental factors, often requiring trained personnel and lacking traction customization, which can lead to suboptimal performance and wear patterns.
Innovation Solution
A system that uses sensor data and light intensity analysis to generate a computational traction profile, allowing for the creation of a customized outsole pattern with improved traction characteristics, optimized for individual performance and environmental conditions, using manufacturing processes like laser cutting and 3D printing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mass-produced standardized shoes are manufactured, then manufacturing cost and productivity are improved, but customization capability and performance optimization for individual athletes deteriorate
Solution Approach 1:
The system performs preliminary data collection and analysis of athlete performance characteristics before manufacturing begins. Sensors capture movement data, pressure distribution, and performance metrics during athletic activities, which are then analyzed to generate customized outsole patterns. This preliminary action enables personalized customization without disrupting mass production workflows.
Solution Approach 2:
The system creates digital copies of athlete-specific performance data and movement patterns to generate customized outsole designs. By capturing and replicating individual athletic characteristics through digital modeling, the system can produce personalized traction patterns while maintaining efficient manufacturing processes.
2Device complexity
If static analysis and limited-time measurements are used for customization, then manufacturing complexity is reduced, but accuracy of performance characterization and long-term adaptation capability deteriorate
Solution Approach 1:
The system implements continuous feedback loops where sensors mounted on shoes collect ongoing performance data during actual athletic use. This feedback mechanism captures long-term performance characteristics, environmental variations, and wear patterns, enabling progressive refinement of customized outsole patterns based on real-world usage data rather than single-time measurements.
Solution Approach 2:
The system transitions from static analysis to dynamic measurement by capturing performance data during actual athletic movements and activities. Sensors record real-time pressure distribution, force vectors, and movement patterns, providing accurate characterization of athlete-specific mechanics under actual loading conditions rather than static postures.
3Manufacturing precision
If laboratory-based analysis is performed, then measurement control is improved, but environmental context information and real-world performance data deteriorate
Solution Approach 1:
The system uses sensors and data processing algorithms as intermediaries to bridge laboratory-controlled measurement precision with real-world environmental context. Sensors capture both controlled performance metrics and uncontrolled environmental variables (terrain, weather, surface conditions), integrating them into comprehensive performance models that maintain measurement accuracy while incorporating ecological validity.
4Ease of manufacture
If standardized tread patterns are used for all shoes, then manufacturing simplicity is improved, but traction optimization for individual performance characteristics deteriorates
Solution Approach 1:
The system applies local quality by customizing specific regions of the outsole based on localized pressure distribution and traction requirements. Different areas of the outsole receive tailored traction patterns optimized for specific functional zones (heel, midfoot, forefoot) based on individual athlete pressure maps and movement characteristics, rather than applying uniform patterns across the entire sole.
Solution Approach 2:
The system modifies outsole parameters (traction element size, spacing, depth, orientation) based on analyzed performance data. By varying these parameters according to individual athlete characteristics and specific performance requirements, the system optimizes traction reliability while maintaining manufacturing feasibility through systematic parameter adjustment rather than complete redesign.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables the production of shoes with enhanced traction and performance customization, adapting to individual movements and environmental factors, thereby improving athletic performance and extending the life of the footwear.
Implementation Method 1
A sensor module 102 is provided. The sensor module 102 is configured to measure light intensity and determine pressure data for an individual based on the light intensity
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The present invention relates to a method of manufacturing an outsole comprising receiving light intensity data obtained by at least one sensor module on which an individual performs an activity, correlating the received light intensity data with a traction characteristic, building a computational traction profile in response to the correlation, creating, in response to the computational traction profile, a visual outsole pattern and producing the outsole based on the visual outsole pattern.