LIDAR Freight Dimensioning for Shipping Cost Optimization
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Solution Overview
Problem
The freight industry faces challenges in accurately calculating shipment costs due to the use of generic rating systems that do not account for shipment density or dimensions, leading to expensive surcharges and inefficiencies.
Innovation Solution
A sensor-based 'dimensionalizer' system that uses Light Detection and Ranging (LIDAR) cameras to determine the weight, dimensions, and shipping parameters of freight units, coupled with a computer-based recommendation engine that suggests adjustments to reduce shipping costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If generic rating systems are used that consider only total weight and class, then pricing simplicity is improved, but measurement precision deteriorates because shipment density and dimensions are not accounted for
Solution Approach 1:
The patent replaces manual measurement methods with automated LIDAR scanning technology to capture three-dimensional dimensions of freight units. The LIDAR system uses light detection and ranging to precisely measure length, width, height, and volume without physical contact, substituting traditional mechanical measuring tools and manual processes with optical sensing and computational geometry.
Solution Approach 2:
The system transitions from considering only weight and class parameters to incorporating density-calculated parameters (volume, dimensions, weight distribution). By calculating density as a derived parameter from multiple measurements, the system enables more accurate pricing classifications while maintaining computational efficiency through automated formulas.
2Measurement precision
If LIDAR cameras and multiple sensors are deployed to accurately measure dimensions and weight, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent integrates LIDAR cameras, weight sensors, and computer vision systems into a unified measurement platform. Multiple sensing modalities are merged to capture complementary data - LIDAR for external dimensions, weight sensors for mass, and computer vision for internal volume estimation - creating a comprehensive measurement system that leverages the strengths of each component while sharing processing infrastructure.
Solution Approach 2:
The system uses computer-generated three-dimensional models and virtual representations of freight units to replicate physical measurements in digital space. By creating accurate digital twins of the cargo, the system enables virtual measurement, analysis, and optimization without requiring physical manipulation or additional sensing hardware during the measurement process.
3Loss of energy
If accurate density calculation is implemented to reduce shipping costs, then loss of energy is improved through cost savings, but difficulty of detecting and measuring increases due to obscure pricing rules
Solution Approach 1:
The system implements feedback loops where measured dimensions and weight data are continuously processed through pricing algorithms to generate cost estimates. The system compares different packaging configurations and provides feedback on which arrangements yield lower shipping costs, enabling iterative optimization of freight unit density and packaging decisions based on real-time cost calculations.
Solution Approach 2:
The system performs preliminary density calculations and cost analyses before the actual shipping process. By measuring and calculating optimal packaging configurations in advance, the system identifies cost-saving opportunities and recommends adjustments to freight unit assembly before cargo is loaded onto vehicles, preventing expensive last-minute changes and ensuring optimal pricing classification.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides accurate measurements of freight units, enabling dynamic recommendations that optimize shipping costs by adjusting dimensions or density, thereby minimizing expenses and avoiding unexpected charges.
Implementation Method 1
at least one Light Detection and Ranging (LIDAR) camera to determine the weight, dimensions, and other shipping parameters of freight units
Data Source
AI summary
Systems and methods provide real-time shipping optimization recommendations for reducing the cost of shipping freight units in a shipment. System comprises a measurement system in communication with a computer system that comprises a client computer device in communication with a host computer system. The measurement system comprises multiple sensing devices, including a plurality of Light Detection and Ranging (LIDAR) cameras, to determine weight, dimensions, and other shipping parameters of the freight units in the shipment. The computer system computes a current shipping cost and density based on the shipping parameters. The computer system determines shipping recommendations including recommended adjustments to the shipping parameters that reduce the current shipping cost. The shipping recommendations are transmitted to the client computer device prior to loading the shipment onto a carrier vehicle for the shipment.