Refrigerated Food Inventory Tracking with 3D Mapping
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Solution Overview
Problem
Traditional methods for maintaining inventory in restaurants are prone to human error, time-consuming, physically strenuous, and fail to accurately predict perishable goods' shelf life and purchasing trends, leading to inefficiencies, resource waste, and potential liability.
Innovation Solution
A food inventory tracking system using rear- and forward-facing cameras and load cell sensors within a refrigerated storage compartment to create a 3D location map, identify food items, calculate quantities, and provide real-time inventory data, reducing manual labor and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inventory examination is used, then employees can identify stock levels, but human error increases and time consumption increases
Solution Approach 1:
The patent replaces manual mechanical inventory examination with an automated optical scanning system using cameras and image processing algorithms. The system automatically captures images of inventory items, identifies them through pattern recognition, and calculates quantities without human intervention, thereby eliminating human error and reducing time consumption.
Solution Approach 2:
The inventory system performs self-examination through automated image capture and processing. The cameras continuously monitor stock levels, and the processing system automatically identifies items and calculates quantities, enabling the system to serve itself without requiring employee intervention for routine inventory checks.
2Measurement precision
If manual weighing of heavy ingredients is performed, then stock quantities can be measured, but employee physical strain increases and time consumption increases
Solution Approach 1:
The patent replaces manual weighing operations with automated optical measurement systems. Cameras capture images of ingredient containers, and image processing algorithms automatically determine volume and weight based on visual characteristics, container dimensions, and ingredient density, eliminating the need for employees to physically handle and weigh heavy items.
Solution Approach 2:
The system introduces an intermediary computational model that translates visual information from camera images into quantitative measurements. This intermediary processing layer converts optical data into accurate stock quantity estimates without requiring direct physical interaction with the ingredients, thereby reducing employee physical strain.
3Adaptability or versatility
If complex inventory variables are manually tracked, then comprehensive inventory management is achieved, but prediction accuracy decreases due to human limitations
Solution Approach 1:
The system implements continuous feedback loops where inventory data is constantly captured, analyzed, and used to update predictions. The automated system monitors stock levels, usage patterns, and external factors in real-time, adjusting predictions dynamically based on actual performance data, thereby improving accuracy while maintaining comprehensive tracking of multiple variables.
Solution Approach 2:
The system dynamically adjusts prediction parameters based on changing conditions such as seasonal variations, supplier lead times, and historical sales data. By automatically modifying these parameters rather than using fixed manual estimates, the system achieves higher prediction accuracy while comprehensively managing multiple inventory variables simultaneously.
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
Facilitates rapid and accurate inventory management, reducing waste, man-hours, and resource consumption while minimizing the risk of errors and injuries, thus enhancing operational efficiency and reducing costs.
Implementation Method 1
at least four load cell sensors located within the refrigerated food storage compartment, wherein the at least four load cell sensors are configured for taking weight measurements of food stored within the refrigerated food storage compartment
Implementation Method 2
at least four rear-facing cameras located at a forward end of the refrigerated food storage compartment, wherein the cameras are configured for capturing images of food stored within the refrigerated food storage compartment
Data Source
AI summary
A food inventory tracking system within a refrigerated food storage compartment includes cameras configured for capturing images of food, load cell sensors for taking weight measurements of food and a computing system for reading images from the cameras and weight measurements from the load cell sensors, generating a three-dimensional location map of an interior of the refrigerated food storage compartment, mapping the images and weight measurements to segments of the three-dimensional location map, such that each segment of the three-dimensional location map is associated with images and weight measurements, identifying a type of food item within said segments based on the images and weight measurements associated with said segment, calculating a current amount of said food item based reporting to a user the type of said food item and the amount of said food item.