Gyro-Enabled Capsule Stabilizes Liquid Cargo During Delivery
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Solution Overview
Problem
Challenges exist in preventing spillage and damage of items with liquid and semi-solid states during transportation due to inertial forces caused by delivery vehicle maneuvers, despite advancements in stabilization technologies.
Innovation Solution
The use of IoT data feeds and machine learning to identify items requiring stabilization, generating packaging instructions, and scheduling delivery with a gyro-enabled capsule to mitigate inertial effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If delivery vehicles perform maneuvers to transport packages, then delivery speed and efficiency are improved, but inertial forces cause spillage and damage to liquid and semi-solid items
Solution Approach 1:
A gyroscopic stabilization system is introduced as an intermediary device between the delivery vehicle and the cargo. The gyroscopic capsule acts as a mediator that absorbs and counteracts inertial forces generated during vehicle maneuvers, preventing these forces from directly affecting liquid and semi-solid items. The gyroscopic device creates a stable reference frame that isolates the cargo from harmful vibrations and shocks while allowing the vehicle to maintain its delivery speed and efficiency.
2Object-affected harmful factors
If stabilization technologies are applied to delivery vehicles, then spillage prevention is improved, but device complexity increases
Solution Approach 1:
The stabilization system is segmented into modular gyroscopic capsules that can be independently deployed for specific cargo types. Rather than implementing a complex whole-vehicle stabilization system, the solution divides the cargo space into separate compartments, each equipped with individual gyroscopic stabilizers. This segmentation allows stabilization functionality to be added only where needed, reducing overall system complexity while effectively preventing spillage of liquid and semi-solid items.
Solution Approach 2:
The gyroscopic stabilization system is designed with multi-functionality to reduce complexity. The same gyroscopic capsules that provide stabilization during transport also serve as protective containment structures for the cargo. Additionally, the system can adapt its stabilization level based on cargo type, providing enhanced stabilization for liquid items while using minimal intervention for solid packages, thereby simplifying control mechanisms.
3Measurement precision
If IoT data feeds and machine learning are used to identify items requiring stabilization, then delivery accuracy is improved, but information processing time increases
Solution Approach 1:
The system performs preliminary classification of cargo types using IoT sensors and machine learning algorithms before the delivery vehicle departs. During the packing phase, item characteristics such as viscosity, container type, and fragility are analyzed and stored in advance. This preliminary action allows the stabilization system to be pre-configured with appropriate settings for each cargo type, eliminating the need for time-consuming real-time analysis during delivery operations and maintaining high identification accuracy.
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
Effectively prevents spills and damage by stabilizing delivery vehicles using gyro-enabled capsules, ensuring safe transportation of amorphous items.
Implementation Method 1
scheduling delivery of the delivery item with a delivery vehicle that includes a gyro-enabled capsule
Implementation Method 2
inertial forces caused by maneuvers of delivery vehicles
Data Source
AI summary
Aspects of the present invention disclose a method for identifying items that can utilize stabilized delivery in a delivery system. The method includes one or more processors obtaining data indicating a delivery item from an internet of things (IoT) enabled device. The method further includes determining information associated with the delivery item. The method further includes determining whether the information of the delivery item is associated with stabilized delivery. The method further includes scheduling delivery of the delivery item with a delivery vehicle, based at least in part on the information associated with the delivery item.