Geolocation-Based Image Notification System with Exclusion Filters
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Solution Overview
Problem
Current technologies lack an effective method to alert mobile device users about images of interest captured in geographical proximity, incorporating facial recognition and augmented reality to provide relevant images based on user profiles and social networking data.
Innovation Solution
A system that uses a server device to identify images of interest by analyzing user profiles, social graph information, and image metadata, sending notifications to mobile devices when the user arrives at locations where relevant images are captured, with features like exclusion scenarios and promotional biases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system analyzes user profiles, social graph information, and image metadata to identify relevant images, then the relevance and personalization of image recommendations is improved, but the computational complexity and processing time increase
Solution Approach 1:
The system segments the image identification process into multiple independent modules: geographical location analysis, facial recognition, social graph evaluation, and metadata processing. Each module handles a specific aspect of image relevance independently, allowing the system to manage complexity through modular design while maintaining comprehensive analysis capabilities.
Solution Approach 2:
The patent introduces exclusion scenarios as intermediary filters that mediate between the comprehensive image analysis and final image selection. These exclusion scenarios (time-based, location-based, activity-based) act as intermediate processing layers that refine the image set without requiring complete re-analysis of all images, thus managing computational complexity while maintaining recommendation quality.
2Loss of time
If the system provides real-time image notifications when users arrive at locations with captured images, then the timeliness and user experience are improved, but the energy consumption and device resource usage increase
Solution Approach 1:
The system employs periodic location checking rather than continuous monitoring, where the mobile device checks for new images at predetermined time intervals or when specific triggering conditions are met. This periodic approach maintains timely notification capability while significantly reducing energy consumption compared to continuous real-time monitoring.
Solution Approach 2:
The system allows users to configure their own notification preferences, exclusion scenarios, and monitoring parameters, enabling the notification system to adapt to user needs and minimize unnecessary energy consumption. Users can self-manage when and where they receive notifications, reducing overall system energy usage by avoiding notifications during excluded periods or locations.
3Measurement precision
If the system implements multiple exclusion scenarios (time windows, activities, locations), then the precision of image notification delivery is improved, but the number of processing parameters and system complexity increase
Solution Approach 1:
The exclusion scenarios are segmented into distinct, independently configurable categories: time-based exclusions, location-based exclusions, and activity-based exclusions. Each category is handled by a separate processing module with dedicated parameters, allowing the system to achieve high notification precision through multiple exclusion criteria while managing complexity through clear separation of concerns and modular parameter management.
Data Source
AI summary
Methods, systems, and devices are described for identifying images which may be of interest to a user based on their current geographic location. In some embodiments, a check is first performed to determine if the current geographic location is a location-of-interest. Images are searched that are in geographical proximity to the current geographic location of the user to identify images-of-interest. The images-of-interest may be designated in part based on actions taken by subjects having had interactions with the images. The user is notified based on the discovery of one or more images-of-interest. The one or more images-of-interest may be presented to the user through the use of map overlays and/or augmented reality techniques.