Automated Carbon Emission Calculation for Shipment Scheduling
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Solution Overview
Problem
Current systems for tracking and managing carbon emissions in transportation are not time-efficient and prone to human error, making it difficult for providers to allocate resources effectively.
Innovation Solution
A system comprising a processor and memory that receives customer requests for shipments, calculates carbon emissions based on shipment elements, and generates a proposed shipment schedule to minimize carbon footprint, utilizing machine-learning modules to optimize routes and transportation methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual tracking systems are used for shipments, then implementation is simple, but time efficiency is poor and human error increases
Solution Approach 1:
The patent replaces manual tracking systems with an automated computational system that uses processors to calculate carbon emissions and generate shipment schedules. This substitution of mechanical/manual operations with automated computational processes directly improves time efficiency while reducing human error, resolving the contradiction between simplicity and productivity.
2Measurement precision
If automated carbon emission calculation systems are implemented, then accuracy and efficiency improve, but system complexity increases
Solution Approach 1:
The system performs self-service by automatically calculating carbon emissions and generating optimized shipment schedules without requiring external intervention. The processor autonomously processes customer requests, calculates emissions based on shipment elements, and produces proposed schedules, thereby improving measurement precision while managing complexity through automation.
Solution Approach 2:
The system incorporates feedback mechanisms where carbon emission calculations inform shipment schedule optimizations, which in turn affect future emission calculations. This closed-loop feedback enables continuous improvement of both accuracy and efficiency while the system learns from past performance data.
3Productivity
If traditional shipment scheduling is used, then operational simplicity is maintained, but resource allocation efficiency deteriorates
Solution Approach 1:
The system changes key parameters by incorporating carbon emission metrics into shipment scheduling decisions. By using carbon emission data as a optimization parameter, the system generates schedules that improve resource allocation efficiency and environmental performance, moving beyond traditional scheduling approaches.
Solution Approach 2:
The system performs preliminary actions by calculating carbon emissions and generating optimized shipment schedules before actual shipments occur. This advance planning allows providers to allocate resources efficiently and make informed decisions about transportation methods, routes, and timing before resources are committed.
Data Source
AI summary
An apparatus and methods for determining carbon emissions of a requested shipment are provided. A computing device of apparatus may be configured to receive a customer request for a shipment of a moveable good. In one or more embodiments, computing device may be configured to provide shipment elements of the shipment as a function of customer request. In one or more embodiments, carbon emission data describing carbon emissions of shipment may be determined by computing device as a function of carbon emission data and/or shipment elements.