Dynamic Transaction Card Power Optimization via ML

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Solution Overview

Problem

Dynamic transaction cards face challenges in optimizing operational configurations and user experiences while extending energy storage life and detecting system or device defects, as existing technologies do not effectively manage power depletion and user behavior associated with various operational configurations.

Innovation Solution

The implementation of a system that uses data inputs from dynamic transaction cards, such as sensor inputs, connection data, and transaction data, to determine optimal configurations and detect defects, employing regression and machine learning algorithms to optimize energy storage life and user experiences, and transmit data to user devices and backend servers for continuous optimization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If various operational configurations and functions are enabled in dynamic transaction cards, then user experience and functionality are improved, but power components are depleted faster

Engineering Contradiction:

Improveoperational configurationsVSAvoidpower components depletion

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The patent implements dynamic adjustment of operational configurations based on real-time power status. The system continuously monitors power component charge levels and automatically adapts display brightness, sensor activation, and communication modes to match available power, allowing full functionality when powered and reduced functionality when power is low

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes operational parameters such as display brightness levels, sensor sampling rates, and communication transmission power based on detected power status. When power components are sufficiently charged, higher power consumption modes are enabled; when charge drops below thresholds, the system transitions to lower power consumption modes

Inventive Principle:

Principle #35Parameter changes

2Reliability

If continuous monitoring and data transmission are implemented, then defect detection capability is improved, but energy consumption increases

Engineering Contradiction:

Improvedefect detectionVSAvoidenergy consumption

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system implements periodic monitoring of configuration and functionality data at scheduled intervals rather than continuous monitoring. Data transmission occurs periodically or event-triggered, reducing overall energy consumption while maintaining adequate defect detection capability through regular system state assessments

Inventive Principle:

Principle #19Periodic action

Solution Approach 2:

The system monitors its own operational status and power levels, using this feedback to adjust monitoring frequency and data transmission timing. When power status is good, more frequent monitoring and transmission occur; when power is low, the system reduces monitoring intensity and transmits only critical data

Inventive Principle:

Principle #23Feedback

3Ease of operation

If optimal configurations are determined through machine learning algorithms, then user experience is optimized, but computational resources and processing time are consumed

Engineering Contradiction:

Improveuser experienceVSAvoidprocessing time

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system collects and stores configuration and functionality data during normal operation, performing data aggregation and preliminary processing in advance. Machine learning algorithms are executed during low-power periods or background processing windows, preparing optimization recommendations before they are needed, thus minimizing real-time processing delays

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS10210505B2Dynamic transaction card optimization

Publication Date: 2019.02.19 CAPITAL ONE SERVICES LLC

AI summary

The present disclosure relates to devices and methods relating to an optimized electronic transaction card where various data inputs associated with a dynamic transaction card optimize operational configurations and/or a user experience of the dynamic transaction card to extend an energy storage life of the dynamic transaction card, promote various behaviors, and/or detect system and/or device defects. A dynamic transaction card may include a dynamic transaction card with various configuration and/or functionality that use the power components (e.g., printed circuit board (PCB), energy storage component, battery, and/or the like) of the dynamic transaction card. The configuration and/or functionality data may include, for example, sensor input, connection data, transaction data, display data, and/or the like. The configuration and/or functionality data may then be used to determine optimal configuration settings.