Location-Specific NFTs for Immersive Venue Experience Capture
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Solution Overview
Problem
Conventional methods for memorializing experiences at venues like sports stadiums and theme parks often distract users and fail to capture the experience from their specific perspective, lacking immersion and personalization.
Innovation Solution
The development of automated systems and methods for creating location-specific non-fungible tokens (NFTs) that capture and memorialize user experiences, allowing users to own digital assets tied to specific locations or events, including their perspective as an observer or participant, using cameras and secure digital ledgers like blockchain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users manually take pictures or video to memorialize experiences, then they can capture the experience, but it distracts users and fails to depict the individual taking the pictures
Solution Approach 1:
The system enables self-service by automatically capturing user perspective footage through device cameras and generating NFTs without requiring user intervention. The automated processing includes stitching multiple camera feeds, adding user identification, and minting NFTs, allowing users to obtain personalized memorabilia while remaining immersed in the experience.
Solution Approach 2:
The system performs preliminary actions by pre-positioning multiple cameras at strategic locations, pre-configuring capture parameters, and pre-establishing the NFT minting infrastructure. This preparation enables automatic capture and processing when users arrive at venues, eliminating the need for users to manually set up equipment or initiate capture processes.
2Loss of information
If conventional memorialization methods are used, then experiences can be recorded, but they fail to capture the specific perspective of the user
Solution Approach 1:
The system segments the memorialization function into multiple independent camera units positioned at different locations, each capturing specific perspective data. This segmentation allows the system to collect comprehensive multi-angle footage while keeping individual camera devices simple and manageable. The segmented approach also enables parallel processing of multiple user perspectives simultaneously.
Solution Approach 2:
The system introduces an intermediary processing layer that receives raw footage from multiple cameras, stitches them together, adds user identification metadata, and prepares the composite video for NFT minting. This intermediary layer abstracts the complexity from users, who only need to interact with simple mobile device interfaces while the complex processing occurs automatically in the background.
3Extent of automation
If automated NFT generation is implemented, then user perspective is captured, but system complexity increases
Solution Approach 1:
The system implements a universal processing platform that handles multiple functions: capturing footage from various camera sources, stitching multiple video feeds, adding user metadata, generating NFTs, and managing digital wallet integrations. This multi-functional approach consolidates complexity into a single automated system rather than requiring separate manual processes for each function.
Solution Approach 2:
The system replaces manual mechanical processes (users physically taking photos, manually editing videos, manually creating NFTs) with automated digital processing. Machine learning algorithms automatically stitch camera feeds and identify user perspectives, while smart contracts on the blockchain automatically mint NFTs based on processed video data, eliminating the need for manual intervention in complex tasks.
Data Source
AI summary
According to one exemplary implementation, a system includes a hardware processor and a system memory storing a software code. The hardware processor is configured to execute the software code to receive, from a user device, a request for a non-fungible token (NFT) based on the presence of a user of the user device in a venue, receive sensor data identifying a location of the user device, and obtain camera data from the venue, the camera data depicting at least one of the user of the user device or a field of view of the user relative to the venue. The hardware processor is further configured to execute the software code to mint the NFT, using the sensor data and the camera data, wherein the NFT depicts at least one of a portion of an object situated within the venue or an event occurring at the venue.