Transport Data Aggregation Using Stage Subgroups for Route Changes

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Solution Overview

Problem

Modern supply chains face inefficiencies when altering delivery routes due to external factors, leading to suboptimal performance.

Innovation Solution

An apparatus and method for transport data aggregation that includes a processor and memory to receive, aggregate, and generate routing data based on transport data, displayed through a graphical user interface, utilizing machine-learning and fuzzy logic to optimize route adjustments.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If delivery routes are altered to respond to external factors, then adaptability is improved, but efficiency deteriorates

Engineering Contradiction:

ImproveadaptabilityVSAvoidefficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system performs preliminary actions by pre-calculating alternative routes and preparing routing data in advance using machine learning models. When disruptions occur, the system can quickly implement pre-prepared alternative routes without needing to recalculate everything from scratch, thus maintaining efficiency while improving adaptability to external factors

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms by continuously monitoring transport data, comparing actual performance against predefined criteria, and using this information to refine future routing decisions. The feedback loop allows the system to learn from past disruptions and optimize future route alterations, balancing adaptability with efficiency

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If route adjustments are made frequently, then adaptability is improved, but loss of time increases

Engineering Contradiction:

ImproveadaptabilityVSAvoidtime

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system performs preliminary route planning and alternative route preparation in advance, so when disruptions occur, the system can quickly implement pre-prepared alternatives without time-consuming recalculation. This preliminary action reduces the time loss associated with frequent route adjustments while maintaining high adaptability

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces manual or mechanical route adjustment processes with automated machine learning models and algorithms. This substitution enables rapid, intelligent decision-making for route adjustments, reducing the time required to respond to disruptions while maintaining adaptability to changing conditions

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12474176B2Apparatus and method of transport data aggregation

Publication Date: 2025.11.18 HAMMEL

AI summary

An apparatus and method for transport management is presented. The apparatus may include at least a processor and a memory communicatively connected to the at least a processor. A memory may include instructions configuring at least a processor to receive transport data of a transport. Processor may be configured to categorize the transport into a stage subgroup as a function of the transport data. Processor may be configured to communicate transport data of a stage subgroup to at least a transport entity. Processor may be configured to generate a data query requesting or searching for updated transport data of the transport. Processor may be configured to update the one or more stage subgroups as a function of the data query.