Social Media Post Temporal Accuracy via IoT Proximity Detection
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Solution Overview
Problem
Social media platforms lack the ability to accurately indicate the point in time of social media posts, preventing users from viewing temporal insights and interactions related to shared information, such as when friends joined or left an event.
Innovation Solution
A method that captures and publishes geographic locations and timestamps of social media posts, detects additional users within proximity, and updates the post with temporal aspects, allowing for enhanced user interfaces with time filtering via a scroll bar, leveraging IoT sensors and GPS for real-time location tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If social media platforms capture and publish geographic locations and timestamps of posts, then temporal and geographical accuracy of social media events is improved, but device complexity and data processing requirements increase
Solution Approach 1:
The patent introduces an intermediary system comprising server computers that receive location and timestamp data from mobile devices, process this information, and publish it to social media platforms. This intermediary layer handles the complexity of data processing, matching, and temporal aspect calculation, thereby improving measurement precision without burdening the end-user devices with excessive complexity.
Solution Approach 2:
The system segments the functionality into distinct components: mobile devices capture raw location and timestamp data, server computers process and match this data with social media posts, and the social media platform presents the processed temporal aspects to users. This segmentation allows each component to specialize in specific tasks, improving overall system precision while distributing complexity across multiple independent modules.
2Loss of information
If the system detects additional users within proximity and updates posts with temporal aspects, then user engagement and interaction tracking are improved, but loss of time for data processing and communication increases
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and pre-processing location data from users' devices even before social media posts are created. When a user makes a post, the temporal aspects and proximity information are already prepared and can be quickly matched, significantly reducing the real-time processing delay and allowing rapid update of interaction visibility.
Solution Approach 2:
The system implements feedback mechanisms where processed temporal and proximity information is continuously updated and reflected back to users in real-time. This feedback loop allows the system to optimize data processing by learning from user interactions and adjusting the frequency and depth of proximity detection, thereby reducing unnecessary processing time while maintaining comprehensive interaction tracking.
3Loss of information
If real-time location tracking and proximity detection are implemented, then temporal insights and interaction tracking are improved, but use of energy by devices increases
Solution Approach 1:
The system implements partial action by selectively activating full proximity detection and temporal tracking only when relevant social media activities occur (e.g., when a user creates a post or checks in at a location). During other times, location data is captured at lower resolution or at less frequent intervals, significantly reducing energy consumption while maintaining sufficient temporal insights for social media purposes.
Data Source
AI summary
A computer-implemented method for updating one or more temporal aspects of a social media post. The computer-implemented method captures a geographic location of a first computing device of a first user and a time stamp associated with a social media post of the first user, and posts the geographic location and the time stamp associated with the social media post of the first user. The computer-implemented method further detects one or more additional computing devices of one or more additional users within a defined proximity of the first user, and updates the social media post of the first user with one or more temporal aspects associated with the detected one or more additional computing devices of the one or more additional users.