Data Aggregation System with Adaptive Thresholds

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Solution Overview

Problem

Current data collection systems in distributed environments face challenges in managing data transmission efficiently, leading to increased communication bandwidth consumption and energy usage, while striving to provide accurate data to consumers.

Innovation Solution

The implementation of a data aggregation system that utilizes inference models to predict data and dynamically adjusts transmission thresholds based on consumer sensitivity and data trends, allowing for reduced data transmission by transmitting only necessary data when accuracy is critical and conserving bandwidth when less frequent updates are acceptable.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If data transmission frequency is increased to provide accurate data to consumers, then data accuracy is improved, but communication bandwidth consumption and energy usage increase

Engineering Contradiction:

Improvedata accuracyVSAvoidenergy consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system dynamically adjusts the data transmission threshold based on consumer sensitivity and data trends. When data changes exceed the threshold, transmission occurs; otherwise, inference models predict values. This dynamic adjustment optimizes the balance between data accuracy and energy consumption by transmitting data only when necessary.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the transmission threshold parameter adaptively based on consumer sensitivity levels and observed data trends. By adjusting this parameter, the system can reduce transmission frequency for low-sensitivity consumers while maintaining high accuracy for high-sensitivity consumers, thereby reducing overall energy consumption.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If data transmission frequency is increased to provide accurate data to consumers, then data accuracy is improved, but communication bandwidth consumption increases

Engineering Contradiction:

Improvedata accuracyVSAvoidbandwidth consumption

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The system dynamically adjusts the data transmission threshold based on consumer sensitivity and data trends. When data changes exceed the threshold, transmission occurs; otherwise, inference models predict values. This dynamic adjustment optimizes the balance between data accuracy and bandwidth consumption by transmitting data only when necessary.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

Inventive Principle:

Principle #35Parameter changes

3Use of energy by moving object

If data transmission is reduced to conserve bandwidth and energy, then energy consumption and bandwidth usage decrease, but data accuracy for consumers deteriorates

Engineering Contradiction:

Improveenergy consumptionVSAvoiddata accuracy

Core Design Contradiction:

Use of energy by moving objectVSMeasurement precision

Solution Approach 1:

The system uses feedback from consumer sensitivity information and data trend analysis to adjust transmission thresholds. This feedback mechanism ensures that transmission occurs when accuracy is critical while allowing reduced transmission when consumers can tolerate predictions, maintaining data accuracy where needed while reducing overall transmission frequency.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system introduces an inference model as an intermediary between data collection and consumer delivery. The inference model generates predicted values that satisfy consumer needs without requiring actual data transmission, thereby maintaining perceived data accuracy while significantly reducing transmission frequency and energy consumption.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Quantity of substance

If data transmission is reduced to conserve bandwidth and energy, then bandwidth consumption decreases, but data accuracy for consumers deteriorates

Engineering Contradiction:

Improvebandwidth consumptionVSAvoiddata accuracy

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The system dynamically adjusts the data transmission threshold based on consumer sensitivity and data trends. When data changes exceed the threshold, transmission occurs; otherwise, inference models predict values. This dynamic adjustment optimizes the balance between data accuracy and bandwidth consumption by transmitting data only when necessary.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS11720464B1System and method for reduction of data transmission by threshold adaptation

Publication Date: 2023.08.08 DELL PROD LP

AI summary

Methods and systems for managing data collection are disclosed. To manage data collection, a system may include a data aggregator and a data collector. The data aggregator and/or data collector may utilize inference models to predict the future operation of the data collector. To minimize data transmission, the data collector may transmit a representation of data to the data aggregator only if the representation of data falls outside a threshold. The threshold may be adapted by the data aggregator in response to the needs of downstream consumers of the data.