Smart Contract Data Structure for Selective User Feedback Collection
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Solution Overview
Problem
The proliferation of wearable and portable technology for data collection poses challenges in gathering user feedback while ensuring user privacy and relevance, particularly in virtual event contexts, where existing solutions fail to effectively limit data sharing to only user feedback that matches provider interests and is acceptable to users.
Innovation Solution
The implementation of smart contract data structures that combine provider and user portions to specify agreement terms on event contexts and user feedback patterns, enabling AI-driven pattern recognition and classification to automatically enforce data sharing limits, ensuring that only relevant and permitted user feedback is collected and shared.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If user feedback data is collected from wearable devices for event contexts, then provider can obtain relevant user feedback information, but user privacy and data sharing control are compromised
Solution Approach 1:
The smart contract data structure segments user feedback data collection into distinct components: event context detection, user feedback pattern identification, and selective data sharing. This segmentation allows the system to collect comprehensive user feedback while maintaining privacy through controlled, targeted data sharing only for specified event contexts and feedback types that users have authorized.
Solution Approach 2:
The smart contract data structure acts as an intermediary between users and providers, establishing clear agreements on what data can be shared and under what conditions. This intermediary mechanism ensures that user feedback is collected and shared only according to pre-established user permissions and provider needs, thereby protecting user privacy while enabling relevant information exchange.
2Quantity of substance
If all user feedback data is collected for analysis, then comprehensive data availability is improved, but data relevance and user permission compliance deteriorate
Solution Approach 1:
The system extracts and collects only the specific user feedback data that is relevant to the detected event context and permitted by user agreements. Rather than collecting all possible user feedback, the smart contract mechanism selectively extracts only the necessary data elements that match the event context and user permissions, thereby maintaining data relevance while reducing unnecessary data collection.
Solution Approach 2:
The data collection approach applies local quality by tailoring the type and extent of feedback data collected to the specific event context and user permissions. Different event contexts trigger different feedback collection strategies, and user-specific permission settings determine the scope of data gathering, ensuring that data relevance is optimized for each local situation rather than applying a uniform collection approach.
3Measurement precision
If manual review of user feedback is performed, then data accuracy and user permission compliance are improved, but processing time and system complexity increase
Solution Approach 1:
The smart contract data structure enables self-service verification where the system automatically ensures data accuracy and permission compliance through built-in validation mechanisms. The contract structure itself enforces the rules for data collection and sharing, eliminating the need for manual review while maintaining high data accuracy and compliance standards.
Solution Approach 2:
User permissions and data sharing agreements are established in advance through the smart contract structure before data collection begins. This preliminary action of defining clear data sharing rules upfront allows for automatic, real-time compliance verification during data collection, eliminating the need for subsequent manual review and reducing processing time while maintaining accuracy.
Data Source
AI summary
Mechanisms are provided for collecting user feedback information from sensors associated with user devices in accordance with smart contract rules. For an event context for an event, a provider portion of a smart contract is generated. The event context indicates an occurrence within the event that is detected through processing patterns of event data collected for the event, and the provider portion specifies a type of user feedback that is of interest to a provider. For the event context, a user portion of the smart contract is generated, where the user portion specifies a type of user feedback that a user of a user device permits to be shared with the provider. A smart contract comprising the smart contract rules is generated by combining the provider portion with the user portion. Collection of user feedback information from the user device is controlled according to the smart contract data structure.