Smart Sample Containers for Distributed Workflow Tracking
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Solution Overview
Problem
The complexity of microscopy systems and the need for specimen-specific processes make it difficult to track and manage sample evaluation workflows across multiple specimens, and centralized management systems are expensive and prone to failure.
Innovation Solution
Smart sample containers equipped with computing hardware and communication interfaces manage and drive sample evaluation workflows independently, determining and optimizing steps without relying on centralized systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized management systems are used to track and manage sample evaluation workflows, then sample tracking capability is improved, but system cost and complexity increase
Solution Approach 1:
The patent divides the centralized management system into distributed smart sample containers, each independently managing its own workflow. Each container becomes an autonomous unit with local processing capabilities, eliminating the need for a complex centralized system while maintaining tracking functionality through individual container intelligence.
Solution Approach 2:
Smart sample containers are equipped with processors and memory to autonomously determine and execute evaluation workflows without external centralized control. The containers self-manage their own evaluation processes, making decisions about which steps to perform and in what sequence, thereby eliminating dependency on complex centralized management infrastructure.
2Ease of operation
If centralized management systems are used to manage sample evaluation workflows, then workflow management capability is improved, but system reliability decreases
Solution Approach 1:
The patent segments the centralized workflow management into distributed autonomous units (smart containers). Each container independently manages its own workflow using local processors and stored evaluation protocols, eliminating single points of failure associated with centralized systems while maintaining comprehensive workflow management capabilities.
Solution Approach 2:
The system transitions from centralized control parameters to distributed autonomous decision-making parameters. Each smart container changes its operational state to include local processing capabilities, enabling it to autonomously determine workflow steps based on sample characteristics without relying on external centralized coordination.
3Loss of information
If complex centralized systems are implemented, then sample evaluation tracking is improved, but cost increases
Solution Approach 1:
Instead of implementing a single expensive centralized system, the patent creates multiple copies of simplified smart container units, each with embedded processors and workflow management capabilities. This distributed copying approach achieves comprehensive tracking coverage without the high costs associated with centralized infrastructure.
Solution Approach 2:
The patent employs inexpensive smart container units that can be individually replaced or upgraded without affecting the overall system. Each container is a cost-effective autonomous unit that performs complete workflow management locally, eliminating the need for expensive centralized hardware and software infrastructure.
Data Source
AI summary
Systems and methods for using smart sample containers to manage complex sample evaluation workflows, are disclosed. An example method for using a smart sample container configured to manage a sample evaluation workflow according to the present invention comprises, obtaining a sample evaluation workflow for the one or more samples, receiving interactions with external devices, and based on the sample evaluation workflow, and causing the external devices to perform actions to advance the sample evaluation workflow. The smart sample container may further modify the sample evaluation workflow based on results of actions performed by the sample evaluation workflow and/or store information relating to the results of such actions. In this way, the smart sample containers are able to dynamically drive the evaluation of a sample through its sample evaluation workflow.