Predictive Eye Tracking in Multi-Modal Assortment Planning Interfaces
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Solution Overview
Problem
Existing enterprise applications for assortment planning and merchandise planning require users to manipulate large datasets inefficiently, using methods like mice, keyboards, or voice recognition, which are unnatural, inflexible, and distracting.
Innovation Solution
A system that monitors user inputs through eye, head, and hand movements, voice, and tactile interactions, using AI to predict actions and adapt interfaces for enhanced efficiency and ease of use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional input devices (mouse, keyboard, voice recognition) are used for assortment planning, then users can interact with the system, but the interaction becomes inefficient, unnatural, and distracting
Solution Approach 1:
The patent replaces traditional mechanical input devices (mouse, keyboard) with eye-tracking technology that detects eye movements and gaze direction. This substitution allows users to interact with the system through natural eye movements rather than manual device manipulation, making the interaction more natural while maintaining efficiency in data manipulation tasks
Solution Approach 2:
The system introduces an intermediary layer that translates eye movements and gaze patterns into selection and navigation commands. This intermediary processing layer enables natural eye-based interaction while efficiently manipulating large datasets, resolving the contradiction between naturalness and efficiency
2Measurement precision
If users manually sift through large datasets and generate visualizations, then comprehensive analysis is achieved, but significant time is lost
Solution Approach 1:
The system performs preliminary actions by automatically generating visualizations and pre-processing data based on predicted user needs. Eye-tracking technology anticipates which data the user wants to analyze and prepares visualizations in advance, reducing the time users spend on manual data processing while maintaining analysis accuracy
Solution Approach 2:
The system uses feedback from eye-tracking data to continuously adapt and refine data presentations. By monitoring where users look and how long they focus on specific data elements, the system dynamically adjusts visualizations to highlight relevant information, improving both analysis precision and speed
3Loss of information
If the system provides detailed data and controls for comprehensive analysis, then analytical depth is improved, but the interface becomes more complex
Solution Approach 1:
The interface dynamically adapts its complexity based on user behavior patterns detected through eye-tracking. The system adjusts the level of detail and control options presented to users in real-time, providing comprehensive data when needed while simplifying the interface during routine tasks, thus maintaining information completeness without constant interface complexity
Data Source
AI summary
A system and method are disclosed for generating intelligent multi-modal system actions based, at least in part, on predicting a user action and one or more stored user inputs. Embodiments include a database and a computer comprising a processor and memory, the computer is configured to monitor user inputs using one or more sensors and one or more tactile interface devices, detect at least two modes of user input and store the user inputs in the database. The computer is further configured to evaluate the stored user inputs in the database and the at least two modes of user input to generate a system action and generate a system action based, at least in part, on predicting a user action and one or more stored user inputs.