Virtual Image Prediction for Product Lifecycle Simulation
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Solution Overview
Problem
Users face challenges in predicting the future performance and physical changes of products over time due to the mismatch between reviewers' experiences and buyers' anticipated usage, as reviewers may not have experienced the item in similar conditions.
Innovation Solution
A system that utilizes augmented reality (AR) and virtual reality (VR) technologies, combined with Internet of Things (IoT) sensors, to generate and present virtual images predicting the product's progression over time based on current and historical data, user feedback, and environmental conditions, enabling users to visualize the product's expected performance and compatibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If reviewers provide product feedback based on their personal usage experiences, then product reviews are generated, but the mismatch between reviewers' experiences and buyers' anticipated usage conditions reduces prediction accuracy
Solution Approach 1:
The patent segments product feedback into multiple dimensions including usage conditions, environmental factors, time duration, and product performance metrics. This segmentation allows the system to capture diverse usage scenarios separately and match them with buyer requirements more accurately, resolving the contradiction between maintaining diverse usage condition coverage and improving prediction precision.
Solution Approach 2:
The system transforms subjective reviewer experiences into quantifiable parameters such as usage intensity, environmental conditions, and time duration. By changing the parameter representation of product feedback, the system can objectively compare and match reviewer experiences with buyer anticipated usage conditions, thereby improving prediction accuracy while accommodating usage condition variability.
2Measurement precision
If the system collects and processes extensive current and historical product data to generate accurate predictions, then prediction accuracy improves, but system complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-processing and structuring product data during collection, organizing current and historical data into standardized formats with defined schemas. This preliminary structuring reduces the complexity of subsequent data processing and analysis operations, allowing the system to maintain high prediction accuracy without proportionally increasing system complexity.
Solution Approach 2:
The system creates simplified digital representations (copies) of complex product data and usage scenarios. By working with these standardized digital models rather than raw complex data, the system can perform accurate predictions while managing computational complexity through abstraction and model simplification.
3Loss of information
If the system generates detailed virtual images showing product progression over time, then user visualization capability improves, but data processing time increases
Solution Approach 1:
The patent applies partial action by generating virtual images at selected time intervals rather than continuously, and by focusing on key product attributes that change over time. This selective approach maintains comprehensive product change information while significantly reducing the computational time required for image generation compared to creating exhaustive detailed images at every possible time point.
Data Source
AI summary
A method, system, and computer program product for generating a mixed reality simulation is provided. The method includes receiving permission to generate product simulations for a targeted product requested by a user. Current data and historical data associated with the targeted product is received and predicted conditions for the targeted product are generated. Multiple virtual images of the targeted product are generated based on the predicted conditions. The multiple virtual images represent an augmented reality based series of images that predict a progression of physical change over time of the targeted product resulting from exposure to environmental conditions. The multiple virtual images are presented to the user via a virtual user interface of an augmented reality hardware device.