Geographical Media Processing System for Dynamic Content Delivery
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Solution Overview
Problem
Current technologies lack capabilities for effectively processing and managing digital photos in a geographical context, particularly in terms of segmentation, delivery, censorship, and user perspective filtering, which limits user engagement and content organization.
Innovation Solution
A system and method utilizing a computer processor and database to process digital photos by inputting geographic data, segmenting areas, and associating area identifiers, enabling features like photo delivery based on density, crowd-based censorship, and user perspective filtering, as well as non-fungible token processing and dynamic group management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If digital photos are processed and stored in a centralized database without geographical segmentation, then storage and management are simplified, but user engagement and content relevance to specific locations are reduced
Solution Approach 1:
The system segments the geographical area into multiple defined areas and further divides these areas into grid-based cells. Each photo is associated with specific area identifiers and cell coordinates based on its geographical location metadata, enabling organized storage and retrieval without compromising management simplicity.
2Productivity
If all photos are delivered to users without filtering based on location and density, then delivery simplicity is maintained, but content relevance and user engagement decrease
Solution Approach 1:
The system applies different delivery strategies based on local characteristics. Photos are filtered and delivered based on the user's current cell location, the density of photos in that area, and user-defined preferences for specific areas or cell sizes, ensuring relevant content is prioritized.
3Reliability
If photo processing includes comprehensive geographical segmentation and multiple processing steps, then content organization and relevance improve, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-defining geographical areas and their grid cell structures before photo upload. Area identifiers and cell coordinates are assigned to photos during ingestion based on their location metadata, so that when users request photos, the filtering and delivery process can operate on pre-organized data structures.
4Adaptability or versatility
If the system processes photos with detailed geographical data and multiple filters, then user perspective filtering and customization improve, but processing time and computational resources increase
Solution Approach 1:
The system implements partial processing by allowing users to select specific areas, cell sizes, and filter criteria. Not all photos require full processing - the system processes only the subset of photos relevant to the user's current cell location and selected parameters, reducing computational overhead while maintaining filtering capabilities.
Data Source
AI summary
Systems and methods are provided to process a digital photo and other media. An apparatus to process digital photos can include a tangibly embodied computer processor (CP) and a tangibly embodied database. The CP can perform processing including: (a) inputting a photo from a user device, and the photo including geographic data that represents a photo location at which the photo was generated; (b) comparing at least one area with the photo location and associating an area identifier to the photo as part of photo data; and (c) performing processing based on the area identifier and the photo data. Processing can provide for (a) processing media with geographical segmentation; (b) processing media in a geographical area, based on media density; (c) crowd based censorship of media; (d) filtering media content based on user perspective, that can be for comparison, validation and voting; (e) notification processing; (f) processing to associate a non-fungible token (NFT) with a segmented area, which can be described more generally as “token” processing; (g) photo walk processing; and (h) dynamic group processing; for example.