Cloud Logistics System Using Object Location Identification Trigger
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Solution Overview
Problem
Current logistics systems lack efficiency and speed in object location identification, object picking, loading, and delivery, particularly in cloud-based environments, and fail to provide real-time data capture and verification for traceability and compliance with standards like the Foodservice GSI US Standards Initiative.
Innovation Solution
A cloud-based computing system that uses a mobile processor connected to a cloud-based server for object location identification, object picking, and delivery, employing a hand-held object location identification trigger with simple signals to facilitate fast and accurate logistics operations, including data storage and transmission of barcodes, RFID tags, and alpha-numeric codes, enabling instantaneous data capture and verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional logistics systems are used for object location identification, picking, loading, and delivery, then the systems can perform basic operations, but the efficiency and speed are insufficient and productivity is low
Solution Approach 1:
The patent replaces traditional mechanical logistics operations with an automated system using mobile processors, object location identification triggers, and cloud-based servers. This substitution enables automatic object tracking, identification, and logistics management, dramatically improving productivity while reducing the time required for operations.
Solution Approach 2:
The system enables self-service through automatic object location identification using triggers and mobile processors. Objects are automatically tracked and identified without manual intervention, allowing the logistics system to operate autonomously and efficiently, thereby increasing productivity and reducing operational time.
2Reliability
If cloud-based computing systems are implemented for real-time data capture and verification, then traceability and compliance improve, but system complexity increases
Solution Approach 1:
The patent introduces cloud-based servers as intermediaries between mobile processors and the logistics operations. These servers handle data capture, verification, and storage, ensuring traceability and compliance while managing system complexity centrally in the cloud rather than in individual devices.
Solution Approach 2:
The system extracts complex data processing and verification functions from local devices and relocates them to cloud-based servers. This extraction allows local mobile processors to remain simple while maintaining high reliability through centralized cloud-based data capture and verification.
3Ease of operation
If simple hand-held trigger devices are used for object identification, then ease of operation improves and computer training is unnecessary, but measurement precision and data accuracy may be compromised
Solution Approach 1:
The patent replaces simple mechanical triggers with sophisticated mobile processors that integrate object location identification triggers, barcode scanners, RFID readers, and GPS tracking. This substitution maintains ease of operation while dramatically improving measurement precision and data accuracy through advanced sensing and processing capabilities.
Solution Approach 2:
The mobile processor serves multiple functions simultaneously - it acts as a simple trigger response device, barcode scanner, RFID reader, GPS tracker, and data communicator. This multi-functionality ensures ease of operation while maintaining high measurement precision through integrated advanced technologies.
Data Source
AI summary
A cloud computing system for object location, object identification, object picking, object picking by line, object loading onto one or more transport devices, or object delivery that can include using a cloud based server comprising a cloud based processor in communication with a cloud based data storage. The cloud based server can be in communication with at least one mobile processor in communication with a mobile data storage and a display. The method can also include sending instructions to an operator from the cloud based computer to a mobile processor associated with an operator to instruct the operator to perform a logistics operation. The logistic operation can include one or more of object location, object identification, object picking, object picking by line, object loading onto one or more transport devices, and object delivery.