Context-Aware Facility Notifications via Dynamic Display Configuration
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Solution Overview
Problem
Existing methods for presenting information to users within a facility face challenges in securely providing sensitive or private user information, often relying on static displays that lack specificity and relevance, failing to tailor recommendations based on user-specific data.
Innovation Solution
A system that allows users to opt into a notification program using facility devices to capture user characteristic and identification attributes, enabling context-aware notifications that are securely displayed based on the user's location and interactions, without requiring biometric data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static displays are used to present facility information, then the presentation is simple and secure, but the information lacks specificity and relevance to individual users
Solution Approach 1:
The system transitions from static displays to dynamic, context-aware notifications that automatically adapt to user location, characteristics, and real-time situation. The notification content changes based on detected user attributes (age, gender, clothing) and spatial position, enabling personalized information delivery without manual configuration.
Solution Approach 2:
The system performs automated user identification and context analysis without requiring manual user input or registration. The deep learning model automatically detects user characteristics from captured images and determines appropriate notifications, allowing the system to serve itself in identifying and personalizing information for each user.
2Measurement precision
If biometric data is stored to enable personalized notifications, then user identification is accurate, but privacy security is compromised
Solution Approach 1:
The system extracts only the necessary visual characteristics (age, gender, clothing) from user images for notification personalization, while completely avoiding storage of biometric data such as facial recognition templates, fingerprints, or other identifiable biological information. The extracted features are used temporarily for notification generation and then discarded.
Solution Approach 2:
The system uses temporary, disposable visual feature representations rather than permanent biometric databases. The extracted user characteristics are used immediately for notification purposes and then discarded, eliminating the need for long-term storage of identifiable user data and associated privacy risks.
3Adaptability or versatility
If user profiles are created to provide tailored recommendations, then information relevance is improved, but the system requires user registration and profile maintenance
Solution Approach 1:
The system automatically generates user profiles and recommendations by analyzing visual characteristics from captured images in real-time, eliminating the need for manual user registration. The deep learning model autonomously extracts features, determines user characteristics, and generates personalized notifications without requiring users to provide identifying information or maintain profiles.
Solution Approach 2:
The system performs preliminary visual analysis and feature extraction automatically when users enter the facility area, before any interaction is required. The deep learning model pre-processes captured images to identify user characteristics and prepare personalized notifications in advance, so that when users are detected, tailored information is immediately available without prior registration.
4Adaptability or versatility
If generic facility information is displayed, then the presentation is simple and secure, but the information is irrelevant to individual users
Solution Approach 1:
The system applies different notification strategies based on local context and user characteristics. Instead of uniform generic information, the system delivers location-specific, attribute-based personalized notifications (e.g., age-appropriate content, location-relevant recommendations) that adapt to the specific situation and user profile at each moment.
Data Source
AI summary
Systems, apparatuses, methods, and computer program products are disclosed for securely presenting a context-aware user notification to a user using a facility device. An example method includes receiving a user participation request for the user, wherein the user participation request comprises (i) a user characteristic attribute set and (ii) a user identification attribute set and determining a current user location based on the user characteristic attribute set and a temporal image set. The method further includes generating a display configuration set for a facility device indicative of instructions for the facility device for displaying the context-aware user notification based on the current user location. The method further includes generating the context-aware user notification based on the current user location and the user identification set and providing a display message to the facility device, wherein the display message comprises the context-aware user notification and the display configuration set.