Machine Learning Engine for Sensor-Based User Eligibility Verification
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Solution Overview
Problem
Mobile devices face challenges in accurately collecting and verifying user information, making it difficult to determine user eligibility for products or services, especially due to the lack of direct interaction and confirmation of user-provided data.
Innovation Solution
A system that identifies and executes interactive condition evaluation tests on mobile devices using sensors and machine learning to process user data, including social data from various sources, to generate outputs such as eligibility for products or services, discounts, and incentives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional verification methods are used to collect and verify user information, then accuracy of user data can be improved, but the complexity of the process and time required increase significantly
Solution Approach 1:
The patent replaces traditional mechanical verification methods (in-person communication, physical documentation review) with electronic sensor-based detection systems. Sensors capture biometric and behavioral data automatically, substituting manual verification processes with automated electronic measurement and analysis systems that provide accurate user information without requiring complex interpersonal verification procedures
Solution Approach 2:
The system enables users to automatically provide verified information through sensor-based self-measurement. Users perform self-tests using device sensors that automatically capture and transmit data without requiring external verification personnel, allowing users to serve themselves in the information collection and verification process while maintaining data accuracy
2Reliability
If in-person communication and additional documentation are required to confirm accuracy, then reliability of user information improves, but the time and resources required increase
Solution Approach 1:
The system performs preliminary verification actions by having users complete sensor-based tests and provide documentation in advance before the actual information verification is needed. This preliminary data collection and self-verification allows the system to have verified user information ready before it is needed, eliminating the need for time-consuming in-person verification when the actual verification occurs
Solution Approach 2:
The patent substitutes time-consuming mechanical verification processes (in-person meetings, manual document review) with automated electronic sensor-based detection and digital documentation analysis. The system automatically processes sensor data and verifies information through electronic means, dramatically reducing the time required while maintaining or improving reliability through consistent automated measurement
3Measurement precision
If multiple interactive tests are executed to collect condition data, then accuracy of data collection improves, but the complexity of the system increases
Solution Approach 1:
The patent implements a universal testing platform that uses a single multi-functional system to execute various types of interactive tests. The same device and sensor suite can perform different tests (cognitive, motor skills, biometric measurements) through software configuration rather than requiring separate specialized equipment for each test type, reducing overall system complexity while maintaining the ability to conduct multiple accurate assessments
Data Source
AI summary
Methods, computer-readable media, and apparatuses for identifying and executing one or more interactive condition evaluation tests and collecting and analyzing social data to generate an output are provided. In some examples, user information may be received and one or more interactive condition evaluation tests may be identified. An instruction may be transmitted to a computing device of a user and executed on the computing device to enable functionality of one or more sensors that may be used in the identified tests. Upon initiating a test, data may be collected from the one or more sensors. The collected sensor data may be transmitted to the system and processed using one or more machine learning datasets. Additionally, social data may be collected and analyzed using one or more machine learning datasets to generate a social profile. The sensor data and social profile may be used together to generate an output.