Smart Container Orchestration Engine for Dynamic Multi-Carrier Routing
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Solution Overview
Problem
Existing shipping technologies face inefficiencies in dynamic route optimization, security, and reliability, especially in rural areas, where limited carrier options and lack of real-time tracking and adaptation hinder speedy and secure delivery processes.
Innovation Solution
The implementation of smart containers equipped with electronic, mechanical, and communication components that can dynamically update transport processes by leveraging multiple carrier types, including autonomous robots and drones, and utilize real-time tracking and security features to ensure secure and efficient delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional shipping methods are used with limited carrier options, then device complexity is reduced, but delivery speed and reliability deteriorate in rural areas
Solution Approach 1:
The transport process is made dynamic through real-time monitoring and adaptation. The smart container continuously receives status updates from multiple carriers and dynamically adjusts the transport plan by selecting optimal carriers based on current conditions, enabling faster delivery without permanent complexity in the system architecture.
Solution Approach 2:
A centralized management service acts as an intermediary between smart containers and multiple carriers. This mediator coordinates carrier selections, manages handoff points, and processes status data, enabling complex multi-carrier routing while keeping the smart container design relatively simple.
2Reliability
If real-time tracking and monitoring are implemented, then delivery reliability is improved, but loss of information increases due to data management requirements
Solution Approach 1:
The system implements continuous feedback loops where status data from carriers is received in real-time, processed by the management service, and used to adjust transport plans. This feedback mechanism improves reliability by enabling proactive responses to transport issues while systematically managing information flow to prevent data loss.
Solution Approach 2:
The centralized management service performs multiple functions: receiving status data from various carriers, processing this information, selecting optimal carriers, managing handoff coordinates, and communicating with smart containers. This multi-functional approach consolidates data management tasks, reducing information loss through centralized handling.
3Adaptability or versatility
If multiple carrier types are integrated into the transport process, then adaptability is improved, but device complexity increases due to coordination requirements
Solution Approach 1:
The transport process is segmented into discrete segments between handoff points, with each segment handled by a specific carrier. The management service divides the overall transport route into manageable segments, assigning different carrier types to different segments based on their capabilities and current performance, thereby enabling adaptability without overwhelming coordination complexity.
Solution Approach 2:
The centralized management service serves as an intermediary that abstracts the complexity of coordinating multiple carrier types. It manages the interfaces between different carriers, handles handoff logistics, and presents a unified control point to smart containers, thereby enabling high adaptability while containing coordination complexity within the management layer.
4Speed
If autonomous robots and drones are used as carriers, then delivery speed is improved, but reliability deteriorates due to limited operational capacity
Solution Approach 1:
The system merges multiple carrier types including autonomous robots, drones, and traditional carriers into a unified transport ecosystem. The management service combines the speed advantages of autonomous carriers with the reliability of established carriers, selecting the optimal mix for each transport segment based on real-time conditions, thereby achieving both speed and reliability simultaneously.
Data Source
AI summary
A system includes an orchestration engine and a smart container. The system can dynamically update a transport process for transporting the smart container to a destination based on status data to use a combination of multiple carriers. The smart container can report status notifications while the transport process is ongoing. Examples of carriers include national/global carriers, regional/local carriers, gig workers, corporate/contracted carriers, or short-range delivery services such as unmanned autonomous robots, land vehicles, or aerial vehicles (e.g., drones). As such, the system can take advantage of a diverse ecosystem of carriers and adapt the transport process in real-time to optimize for a target parameter such as a time remaining to the destination, a distance remaining to the destination, or a cost to complete the transport process.