Profile-Based Navigation Route Selection
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Solution Overview
Problem
Conventional navigation systems primarily focus on total commute time, neglecting other user preferences that may significantly impact the optimal route selection, such as personal traits, medical conditions, and comfort factors.
Innovation Solution
A profile-based navigation system that generates a user-specific navigation profile by analyzing social media data to identify preferences and characteristics, comparing these to potential routes, and determining the optimal route based on factor values and weights assigned to each route.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional navigation systems select optimal route based on total commute time only, then route selection is simple and fast, but user-specific preferences and characteristics are neglected
Solution Approach 1:
The system performs preliminary actions by generating user profiles in advance through social media network analysis, storing user preferences, characteristics, and behaviors before navigation is needed. This allows the system to quickly match pre-analyzed profiles with route options during actual navigation, resolving the contradiction between customization and complexity.
Solution Approach 2:
The patent introduces an intermediary component - the user profile - that mediates between the complex social media data and the navigation route selection. The profile acts as a simplified representation of user preferences that can be easily compared against route characteristics, reducing the complexity of real-time decision-making while maintaining high adaptability.
2Measurement precision
If navigation system analyzes social media data to generate user profiles, then route selection becomes highly personalized, but data processing time and computational resources increase
Solution Approach 1:
The system performs social media analysis and user profile generation in advance, before the user needs navigation services. By pre-processing the complex social media data and storing it in structured user profiles, the system achieves high measurement precision in matching user preferences to routes without incurring processing delays during actual navigation use.
Solution Approach 2:
The system performs partial analysis by focusing only on relevant social media data elements that pertain to navigation preferences (such as location checks-ins, travel behavior patterns, and stated preferences) rather than analyzing all possible social media content. This selective approach maintains accuracy while reducing processing time and computational resources.
3Reliability
If navigation system considers multiple user preferences and characteristics, then route selection quality improves, but the number of route factors to evaluate increases
Solution Approach 1:
The patent segments the complex route evaluation process into distinct components by organizing user preferences into separate categories (demographics, behaviors, characteristics) and evaluating route factors independently. Each preference category can be matched against corresponding route attributes, allowing the system to consider multiple factors simultaneously while maintaining manageable complexity through modular evaluation.
Solution Approach 2:
The system changes parameters by transforming qualitative user preferences from social media data into quantifiable metrics that can be directly compared with route characteristics. By converting preference data into numerical weights and scores, the system can efficiently evaluate multiple route factors using standardized calculations, improving reliability while controlling the complexity of factor evaluation.
Data Source
AI summary
A computer generates a navigation profile corresponding to a user by identifying one or more user preferences within an associated social media network. The computer receives a user input identifying a starting location and a destination, from which the computer identifies one or more potential routes between the starting location and destination. The computer generates one or more route profiles corresponding to the one or more potential routes detailing one or more characteristics associated with each of the potential routes. The computer then compares the navigation profile associated with the user to the route profiles associated with the one or more potential routes and, based on the comparison, determines an optimal route of the one or more potential routes.