Geolocation Database Enhancement via User Gaze and Emotion Sensing
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Solution Overview
Problem
Current voice-based assistants and geolocation databases do not effectively leverage user information such as speech tone, emotional state, and gaze direction to enhance location-based services, limiting their ability to provide personalized recommendations and real-time updates.
Innovation Solution
A computer-implemented method and system that utilizes sensors within a transportation vehicle to detect user-initiated triggering events, including emotions, gaze, and queries, to update a geolocation database with real-time user feedback and preferences, enabling enhanced location-based services like point-of-interest recommendations and route optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional geolocation databases are used without user feedback integration, then the database structure remains simple, but the quality and personalization of location-based recommendations deteriorate
Solution Approach 1:
The system implements feedback loops where user interactions (visits, emotions, gaze) are continuously collected and used to update the geolocation database. This feedback mechanism enables the database to learn and improve recommendation quality over time while maintaining a structured update process that manages complexity.
Solution Approach 2:
The patent pre-structures the database with specific fields for user feedback, emotions, and gaze data. By preparing these data structures in advance, the system can efficiently integrate user information without requiring complex real-time processing, thus improving recommendation quality while controlling complexity.
2Measurement precision
If multiple sensors are deployed to detect user emotions and gaze, then the accuracy of user state detection improves, but the device complexity and cost increase
Solution Approach 1:
The system uses a multi-functional sensor suite where cameras serve multiple purposes: capturing user gaze direction, detecting facial expressions for emotion recognition, and monitoring user presence. This multi-functionality improves detection accuracy while reducing the need for separate specialized sensors, thereby controlling system complexity.
Solution Approach 2:
The patent combines multiple detection functions (gaze tracking, emotion recognition, presence detection) into an integrated sensor system. By merging these functions and processing them through a unified algorithmic framework, the system achieves high detection accuracy without proportionally increasing system complexity.
3Adaptability or versatility
If real-time user feedback is continuously collected and processed, then the personalization of recommendations improves, but the processing time and energy consumption increase
Solution Approach 1:
The system implements periodic processing of user feedback rather than continuous real-time processing. User interactions are collected and processed at structured intervals (e.g., after completing a visit or at predefined checkpoints), which reduces energy consumption while still enabling effective personalization of recommendations.
Solution Approach 2:
The system pre-processes and filters user feedback data to identify only significant interactions that warrant database updates. By preliminarily filtering out routine or insignificant data, the system reduces the volume of data requiring intensive processing, thereby lowering energy consumption while maintaining personalization effectiveness.
4Adaptability or versatility
If comprehensive user data (emotions, gaze, queries) is aggregated in the geolocation database, then the quality of personalized services improves, but the data privacy and security risks increase
Solution Approach 1:
The system extracts and stores only essential aggregated metrics from user data (e.g., visit frequency, emotion patterns, gaze duration) rather than retaining raw personal information. This extraction approach enables personalized services while minimizing privacy risks by removing identifiable personal data from the database.
Solution Approach 2:
The patent transforms sensitive user data into anonymized parameters and aggregated statistics. By changing the form of data from identifiable personal information to abstracted metrics, the system maintains the utility for personalization while significantly reducing privacy and security risks.
Data Source
AI summary
While current voice assistants can respond to voice requests, creating smarter assistants that leverage location, past requests, and user data to enhance responses to future requests and to provide robust data about locations is desirable. A method for enhancing a geolocation database (“database”) associates a user-initiated triggering event with a location in a database by sensing user position and orientation within the vehicle and a position and orientation of the vehicle. The triggering event is detected by sensors arranged within a vehicle with respect to the user. The method determines a point of interest (“POI”) near the location based on the user-initiated triggering event. The method, responsive to the user-initiated triggering event, updates the database based on information related to the user-initiated triggering event at an entry of the database associated with the POI. The database and voice assistants can leverage the enhanced data about the POI for future requests.