Wearable Device Test Case Execution Using Digital Twin Simulation
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Solution Overview
Problem
Testing gesture-controlled functions in wearable IoT devices is time-consuming and requires actual user interactions, making it inefficient for validating test cases.
Innovation Solution
A computer-implemented method using an artificial human and digital twin to simulate user interactions, analyze movement information, and generate solutions to improve device performance, thereby reducing test case validation time and identifying performance deviations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If actual user interactions are used to test gesture-controlled functions, then test accuracy is improved, but testing time and resource consumption increase significantly
Solution Approach 1:
The patent creates a digital twin that is a virtual copy of the physical wearable device. This digital replica can be interacted with programmatically to simulate user gestures and movements without requiring actual physical users. The digital twin receives and processes the same types of movement data that the physical device would receive, allowing for accurate testing of gesture-controlled functions while eliminating the time consumption of manual user testing.
Solution Approach 2:
The patent pre-configures the digital twin with the device's sensor capabilities, response characteristics, and operational parameters before testing begins. Test scenarios and movement patterns are pre-programmed into the system, allowing automated execution of test cases without requiring real-time human intervention. This preliminary setup enables rapid, repeated testing while maintaining accuracy.
2Reliability
If manual test case execution is performed, then test thoroughness is improved, but productivity and efficiency decrease
Solution Approach 1:
The digital twin system is designed to autonomously execute test cases and evaluate results without requiring continuous human oversight. The system automatically receives movement information, processes it through the virtual device model, generates test results, and can even identify performance deviations. This self-service capability maintains thorough testing while dramatically improving productivity by eliminating manual test execution steps.
Solution Approach 2:
The system implements automated feedback loops where test results are immediately processed and analyzed. The digital twin provides real-time feedback on device performance based on simulated user interactions, allowing for rapid iteration and comprehensive testing. This automated feedback mechanism ensures thorough testing coverage while maintaining high productivity through efficient result processing.
3Productivity
If digital twin simulation is used, then testing efficiency is improved, but device complexity increases
Solution Approach 1:
The digital twin is designed as a universal testing platform that can evaluate multiple different wearable device types and configurations through a single system. The virtual model can be configured to represent different sensor arrangements, processing capabilities, and operational parameters, allowing one digital twin system to test various device iterations without requiring separate physical devices for each test scenario. This multi-functionality improves efficiency while managing complexity through standardization.
Data Source
AI summary
Embodiments of the present invention provide methods, computer program products, and systems. Embodiments of the present invention can, in response to receiving constraints of a test case that test a device, create an artificial interaction that satisfies constraints of the test case. Embodiments of the present invention can then analyze movement information from the created artificial interaction. Embodiments of the present invention can then generate one or more solutions that improve functioning of the device based on the analyzed movement information.


