Sensor-Based Token Transfer Detection Using Movement Pattern Analysis
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Solution Overview
Problem
Existing methods for ensuring that a device is possessed by an authorized person, such as token-based systems, face issues with user comfort, efficiency, and effectiveness, particularly in environments where repeated checks or data collection are cumbersome or invasive.
Innovation Solution
A device equipped with sensors, like accelerometers and gyroscopes, that uses pattern recognition software, like neural networks, to detect and track possession by analyzing movement patterns, ensuring that privileges are granted only to the authorized person.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If personal data collection and comparison methods are used to verify authorized person, then authorization reliability is improved, but processing time and system complexity increase
Solution Approach 1:
The system performs preliminary actions by collecting and analyzing movement patterns during normal device usage to establish a baseline profile of the authorized user. This preliminary characterization enables faster verification later without requiring repeated full data collection processes, thus improving authorization reliability while reducing processing time.
Solution Approach 2:
Instead of collecting and storing extensive personal data, the system creates a simplified copy or representation of the user's movement patterns through the device. This movement profile serves as a lightweight verification mechanism that maintains authorization reliability without the time and complexity overhead of full personal data comparison.
2Reliability
If personal data collection and comparison methods are used to verify authorized person, then authorization reliability is improved, but device complexity and cost increase
Solution Approach 1:
The system replaces complex personal data collection and comparison infrastructure with a simplified movement pattern copying approach. By capturing and analyzing device movement characteristics, the system achieves reliable authorization verification without requiring extensive personnel, equipment, or data management complexity.
Solution Approach 2:
The invention substitutes manual verification processes and complex data comparison systems with automated sensor-based movement analysis. This mechanical-to-digital substitution reduces the need for personnel and substantial equipment at multiple points, thereby reducing device complexity while maintaining or improving authorization reliability.
3Difficulty of detecting and measuring
If human watching and behavior monitoring are used to prevent token exchange, then detection capability is improved, but cost and effectiveness decrease
Solution Approach 1:
The system replaces expensive human watching and behavior monitoring with automated sensor-based detection embedded in the device. The sensors continuously monitor device usage patterns and movement characteristics, enabling effective detection of unauthorized token exchange without the high costs associated with human surveillance infrastructure.
Solution Approach 2:
The device performs self-monitoring of its own usage patterns and movement characteristics without requiring external surveillance infrastructure. This self-service approach to detection capability improves cost-effectiveness by eliminating the need for expensive external monitoring systems while maintaining effective detection of unauthorized exchange.
4Reliability
If body-attached tokens like wristbands or stamps are used, then authorization guarantee is improved, but user comfort and acceptance decrease
Solution Approach 1:
The invention extracts the authorization verification function from physical body-attached tokens and relocates it to the device itself through sensor-based movement analysis. This extraction eliminates the need for uncomfortable wristbands or stamps while maintaining the authorization guarantee, as the device autonomously verifies user identity through movement patterns.
Data Source
AI summary
A method of confirming the identity of a person who issued a token to signify eligibility for a privilege. Possession token is confirmed to be by the same person by using sensors in the token which track the movements of the person. A machine learning system is trained to evaluate the sensor data detecting transfer of possession of the token. The state of continuous possession since the token was issued or set to an enabled state is confirmed and the privilege is granted. The method of identity confirmation is used in various contexts such as for to control entry to a location, use of a facility or service. It is also useful to determine continuous possession of a weapon to prevent misuse after the weapon is stolen, dropped or lost. Servers, beacons and outside sources of data or inputs to be measured by the sensor can also be used.