Food Holding Sensor System with Self-Calibrating Depth Measurement
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Solution Overview
Problem
Existing solutions for managing inventory levels in restaurants are imprecise and costly, as they require employee management and are not autonomous, lacking technologies that can accurately measure and calibrate inventory levels without human intervention.
Innovation Solution
A food processing system that includes a sensor unit for determining holding data of food containers, a processing unit for determining a scheduling state based on current and historical data, and a control unit to control actuators such as robotic processes or personnel to prepare food, enabling autonomous or semi-autonomous management of inventory and production scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If depth sensors are used to measure inventory levels, then measurement capability is improved, but device complexity and calibration requirements increase
Solution Approach 1:
The system performs self-calibration by automatically determining calibration parameters from captured images of food containers without requiring manual intervention. The processing unit analyzes image data to identify container characteristics and automatically adjusts calibration parameters, enabling the sensor system to adapt to different container types and configurations autonomously.
Solution Approach 2:
The system dynamically adjusts calibration parameters based on detected container characteristics. By changing parameters such as depth scaling factors and region of interest boundaries according to the specific container being monitored, the system maintains measurement accuracy across diverse container types without requiring manual recalibration for each scenario.
2Productivity
If manual inventory management is used, then device complexity is reduced, but productivity and precision deteriorate
Solution Approach 1:
The system replaces manual visual inspection and physical inventory counting with automated optical sensing and image processing. Depth sensors and cameras capture images of food containers, and the processing unit automatically analyzes these images to determine inventory levels, eliminating the need for manual intervention while significantly improving measurement precision and productivity.
Solution Approach 2:
The system continuously monitors inventory levels by capturing repeated images and comparing them against previous measurements. This feedback mechanism enables real-time tracking of food depletion rates, automatic generation of replenishment alerts when thresholds are reached, and dynamic adjustment of production scheduling based on actual consumption patterns.
3Measurement precision
If sensor calibration is performed manually, then measurement accuracy can be improved, but loss of time and ease of operation worsen
Solution Approach 1:
The system performs preliminary calibration by automatically capturing images of food containers during normal operation and using these images to determine calibration parameters. Rather than requiring a separate manual calibration step, the system continuously refines its calibration based on actual operational data, maintaining high measurement precision without dedicating specific calibration time.
Data Source
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AI summary
The invention is related to a food processing system, which comprises a sensor unit for determining holding data of at least one pan or holding container placed in a food holding area. The system further comprises a processing unit for determining a scheduling state based on current holding data and/or a holding data history; and a control unit to control an actuator based on the determined scheduling state.