Time Temperature Indicator for Perishable Goods Tracking
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Solution Overview
Problem
Current methods for managing perishable goods supply chains lack efficient, real-time tracking and decision-making capabilities, particularly in determining the freshness and remaining shelf-life of products, which can lead to waste and reduced customer satisfaction.
Innovation Solution
A system and method utilizing hardware processors to read Time Temperature Indicators (TTIs) affixed to perishable goods, processing image data to quantify color changes, and employing machine-learning models to predict remaining shelf-life and freshness, while also integrating GPS and barcode reading for comprehensive supply chain management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional supply chain management methods are used for perishable goods, then operational simplicity is maintained, but real-time tracking capability and decision-making efficiency deteriorate
Solution Approach 1:
The TTI sensor automatically monitors time-temperature exposure and generates visual indicators without requiring external intervention. The system self-registers cumulative exposure data through chemical reactions that progress autonomously based on environmental conditions, eliminating the need for manual tracking while providing continuous real-time information.
Solution Approach 2:
The patent replaces manual inspection and mechanical tracking systems with optical detection methods. Image sensors capture visual changes in the TTI indicator, and machine learning algorithms automatically interpret the colorimetric data to determine freshness status, substituting human judgment and mechanical processes with automated optical and computational systems.
2Measurement precision
If manual inspection methods are used to determine freshness, then system complexity is kept low, but measurement precision and decision-making accuracy deteriorate
Solution Approach 1:
Manual visual inspection is replaced with digital image sensors that capture precise colorimetric data. Machine learning models process the image data to objectively determine TTI status, eliminating human subjectivity and variability. The system automatically quantifies color changes and maps them to freshness metrics, providing consistent and accurate measurements.
Solution Approach 2:
The TTI sensor utilizes time-temperature integrated colorimetric changes as its detection mechanism. The indicator undergoes progressive color transformation based on cumulative exposure to improper temperatures, and this visual change serves as the direct measurement signal for freshness assessment, enabling non-contact optical detection.
3Productivity
If real-time monitoring systems are implemented, then productivity and waste reduction are improved, but energy consumption and operational complexity increase
Solution Approach 1:
Instead of continuous monitoring that would consume constant energy, the system uses periodic image capture at key supply chain nodes. The TTI sensor continuously accumulates time-temperature data passively without power consumption, while active imaging occurs only when goods are transferred or inspected, providing real-time information with intermittent energy input.
Solution Approach 2:
The TTI sensor performs continuous monitoring autonomously without requiring active power input. The chemical reaction progresses automatically based on environmental conditions, storing cumulative exposure information in its visual state. This passive self-monitoring eliminates the need for powered sensors or continuous energy input while maintaining real-time tracking capability.
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
Enables real-time monitoring and decision-making within the supply chain, reducing waste and improving customer satisfaction by accurately assessing product freshness and shelf-life, optimizing inventory, and ensuring compliance with regulations.
Implementation Method 1
The sensors are assembled from a base label (printed aluminized label) and a printed active label that contains an etchant in its adhesive layer. In some embodiments, once the active label is placed on top of the base label, the TTI is activated, and the etching process starts. This process is time and temperature dependent, creating a visual change of the indicator.
Implementation Method 2
A system and method utilizing hardware processors to read Time Temperature Indicators (TTIs) affixed to perishable goods, processing image data to quantify color changes
Data Source
AI summary
A method for management of perishable goods handling, including using a hardware processor for reading and/or recognition and/or monitoring at least one of color change, appearance/disappearance of at least a segment, variation in at least one of pattern, shape and/or size of at least a portion of an indication window of at least one TTI affixed to at least one item of perishable goods, thereby to obtain a TTI reading, and for processing that reading including generating and outputting at least one perishable goods handling command, responsive to at least the TTI reading.