Method for controlling temperature of refrigerator provided in vehicle
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Solution Overview
Problem
Vehicle refrigerators struggle to maintain optimal temperature conditions for food items requiring low-temperature storage, especially when exposed to external heat during transportation, leading to potential food deterioration.
Innovation Solution
A method and device for controlling the refrigerator temperature in a vehicle using image recognition to identify food items needing low-temperature storage, adjusting cooling temperatures based on internal and external conditions, and predicting temperature changes through ANN models, ensuring optimal storage conditions are maintained.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the refrigerator uses a fixed cooling temperature, then the device complexity is reduced, but the foodstuff may deteriorate when exposed to external heat during vehicle transportation
Solution Approach 1:
The system performs preliminary identification of foodstuffs requiring low-temperature storage using image recognition before transportation begins. The ANN model predicts temperature changes based on purchase information and location data, allowing the refrigerator to pre-adjust cooling settings before external heat exposure occurs, ensuring foodstuff preservation without requiring complex real-time adjustment mechanisms
Solution Approach 2:
The system continuously monitors temperature inside the refrigerator using sensors and compares it with target temperatures. Based on this feedback, the control unit dynamically adjusts the cooling system to maintain optimal temperature conditions. The system also uses feedback from image recognition and ANN predictions to refine temperature control strategies during transportation
2Reliability
If the refrigerator dynamically adjusts temperature based on image recognition and ANN predictions, then foodstuff preservation is improved, but the device complexity and energy consumption increase
Solution Approach 1:
The system applies dynamic temperature adjustment selectively only when foodstuffs requiring low-temperature storage are detected through image recognition. Instead of continuously operating at high capacity, the refrigerator adjusts cooling levels based on actual foodstuff presence and predicted temperature changes, reducing unnecessary energy consumption while maintaining preservation reliability
Solution Approach 2:
The system changes operating parameters (cooling temperature, cooling intensity) based on predicted temperature changes from the ANN model and actual temperature sensor readings. By adjusting parameters dynamically rather than maintaining constant high-power operation, the system achieves effective foodstuff preservation with optimized energy consumption
3Adaptability or versatility
If the refrigerator uses simple temperature control without image recognition, then the device complexity is reduced, but the ability to identify and respond to specific foodstuff temperature needs is lost
Solution Approach 1:
The refrigerator system integrates multiple functions into a unified control architecture: image recognition for foodstuff identification, ANN modeling for temperature prediction, sensor monitoring for real-time temperature detection, and adaptive cooling control. This multi-functional integration enables foodstuff-specific temperature control without proportionally increasing overall system complexity, as all functions share common hardware resources and control logic
Solution Approach 2:
The system uses image recognition to automatically identify foodstuffs and their storage requirements without manual input. The ANN model self-adjusts predictions based on learned patterns from purchase information and location data. The control system autonomously adjusts temperature settings based on sensor feedback, eliminating the need for complex manual configuration while achieving high adaptability
4Reliability
If the refrigerator continuously monitors temperature and adjusts cooling in real-time, then foodstuff preservation is improved, but the loss of time for processing and response increases
Solution Approach 1:
The system performs preliminary temperature change predictions using the ANN model based on purchase information, location data, and environmental conditions before the vehicle journey begins. This allows the refrigerator to pre-adjust cooling settings and reduce the frequency of real-time adjustments during transportation, maintaining foodstuff preservation while minimizing processing time losses
Solution Approach 2:
Instead of continuous real-time adjustment, the system uses periodic temperature monitoring at strategically selected intervals. The control unit adjusts cooling settings at these periodic checkpoints based on ANN predictions and sensor readings, achieving effective foodstuff preservation while reducing the time lost to excessive processing and adjustments
Data Source
AI summary
A method for controlling a temperature of a refrigerator provided in a vehicle is provided. A method for controlling a temperature of a refrigerator provided in a vehicle according to an embodiment of the present disclosure detects a foodstuff requiring a low temperature storage included in image information of an article using an artificial neutral network model, and when the foodstuff requiring the low temperature storage is detected, can prevent deterioration of the foodstuff while the article is transported through the vehicle by controlling a temperature of the refrigerator based on storage temperature information of the foodstuff requiring the low temperature storage. A temperature control device of a refrigerator installed in a vehicle of the present disclosure is associated with an artificial intelligence module, an unmmanned aerial vehicle (UAV) robot, an augmented reality (AR) device, a virtual reality (VR) device, and a device related to a 5G service.