Dynamic Data Item Reordering via Sensor Context
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Solution Overview
Problem
Existing technologies fail to effectively determine the optimal display order of data items on mobile computing devices based on contextual data captured by sensor devices, leading to inefficient user interaction and task management.
Innovation Solution
A server and mobile computing device system that utilizes a scoring model to reorder data items based on contextual data, including sensor measurements and user-specific parameters, to prioritize tasks according to user effectiveness and relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data items are displayed in a fixed order, then the display structure is simple, but the relevance to user context is low
Solution Approach 1:
The patent implements dynamic display order determination by continuously monitoring sensor data (location, time, device orientation) and reordering data items based on current contextual conditions. The system transitions from static to dynamic prioritization, where the display order changes automatically according to real-time context changes detected by sensors.
Solution Approach 2:
The system changes the parameter of display order based on sensor data parameters such as location coordinates, time of day, and device orientation. By mapping sensor parameter values to priority levels, the system adapts the display order without requiring complex user input, resolving the contradiction between adaptability and complexity.
2Quantity of substance
If more data items are added to the list, then the quantity of information is increased, but the display order becomes harder to determine optimally
Solution Approach 1:
The patent segments the determination of display order by processing data items in categories based on sensor context. Instead of evaluating all items uniformly, the system divides items into relevant categories (e.g., location-based, time-based) and applies prioritization rules to each segment, making the overall determination more manageable and accurate.
Solution Approach 2:
The system introduces sensor data as an intermediary between the data items and the display order determination. Rather than directly analyzing all data items to determine priority, the sensor measurements serve as a mediator that translates physical context into prioritization rules, simplifying the measurement and determination process.
3Adaptability or versatility
If the display order is frequently adjusted based on sensor data, then the relevance to user context is improved, but the processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing prioritization rules and categories based on sensor data types. Before actual reordering is needed, the system prepares mapping relationships between sensor values and priority levels, enabling faster execution during runtime without requiring complex real-time calculations.
Solution Approach 2:
The display order determination system serves itself by automatically using sensor data to trigger reordering without external intervention. The system monitors sensor changes and autonomously adjusts the display order, eliminating the need for user-initiated sorting operations and reducing overall processing time compared to manual reordering.
Data Source
AI summary
A device receives a request to display a learning module. The device receives sensor values from a set of one or more sensor devices attached to a patient. The device displays a set of survey questions. The device receives user-specified responses to the set of survey questions. The device selects a first learning module from a plurality of learning modules based on the sensor values and the user-specified responses to the set of survey questions. The device displays the first learning module on the display in response to receiving the request to displaying the learning module.