Dynamic AI Geolocation Authentication for Card and Wearable Transactions
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Solution Overview
Problem
Existing resource exchange event authentication systems rely on predefined location rules from mobile devices with Internet and cellular connectivity, failing to account for dynamic circumstances and are not applicable when such devices are unavailable, and lack flexibility in adapting to user-specific conditions.
Innovation Solution
A system using AI and ML to authenticate resource exchange events based on user location determined from short-range wireless signals from a card or wearable device, equipped with RFID, Zigbee, or Bluetooth Low Energy components, allowing for dynamic rule determination and authentication without requiring Internet or cellular connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If location determination uses GPS signals from mobile communication devices, then location accuracy is improved, but device availability and accessibility deteriorate when users do not possess such devices
Solution Approach 1:
The patent applies universality by enabling location determination through multiple device types (mobile communication devices, card devices, and wearable devices) rather than relying exclusively on GPS-capable smartphones. This allows the system to serve diverse user populations including minors and elderly individuals who may not possess smartphones, thereby improving device availability while maintaining location accuracy through alternative signaling mechanisms
Solution Approach 2:
The patent introduces card devices and wearable devices as intermediary elements that can transmit location signals without requiring full mobile communication capabilities. These intermediary devices bridge the gap between users without smartphone access and the authentication system, enabling location-based authentication through short-range wireless signals from nearby devices rather than direct GPS signals from the user's own device
2Device complexity
If authentication rules are predefined in advance, then system simplicity is improved, but adaptability to dynamic circumstances deteriorates
Solution Approach 1:
The patent applies dynamics by transitioning from static, predefined authentication rules to dynamic rules that are determined in real-time based on current circumstances. The system now evaluates location data, transaction details, user history, and environmental factors at the moment of authentication, allowing rules to adapt to changing conditions such as unusual locations, high-risk transactions, or time-of-day variations while maintaining system functionality through automated decision-making
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors authentication outcomes, location data, and transaction patterns to refine and adjust authentication rules dynamically. This feedback loop enables the system to learn from past authentication events and adapt rules based on emerging patterns, risk assessments, and changing user behaviors, thereby improving adaptability while managing complexity through data-driven automation
3Adaptability or versatility
If authentication system supports multiple device types without Internet connectivity, then device accessibility is improved, but system complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the authentication system into distinct functional modules: location determination module that handles various device types, authentication rule evaluation module, and communication module. This segmentation allows each component to specialize in specific tasks and device protocols, managing overall system complexity through modular architecture while supporting diverse device types including card devices and wearable devices that operate independently of Internet connectivity
Data Source
AI summary
Resource exchange event authentication predicated on user location that is determined from short-range wireless signals transmitted from a card or wearable device in possession of the user. Artificial Intelligence (AI), including Machine Learning (ML) techniques are relied on to determine an authentication rule and/or parameters for an authentication rule as part of the authentication process. Thus, at least a portion of the authentication rules and/or parameters, which may be based not only on the aforementioned determined location of the user, but also on other factors such as time, amount of resource exchange event, type of objects/services being exchanged in the event and the like, are determined intelligently and dynamically at the time that the resource exchange event occurs.