Artificial intelligent refrigerator
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Solution Overview
Problem
Conventional refrigerators lack accurate timing and positioning for load correspondence operations due to reliance on temperature sensors, leading to inefficiencies in maintaining optimal temperature variations in refrigerating and freezing compartments.
Innovation Solution
An artificial intelligent refrigerator equipped with multiple temperature sensors and a processor that calculates load accumulation amounts based on internal temperatures, external conditions, and operation states, adjusting cooling ability accordingly, and communicates through 5G networks for optimized temperature control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional refrigerators perform load correspondence operation simply when temperature increases to a predetermined level, then the operation is easy to implement, but the timing and positioning of load correspondence operation cannot be accurate
Solution Approach 1:
The patent divides the temperature sensing function into multiple temperature sensors positioned at different locations (first temperature sensor in the refrigerating compartment, second temperature sensor in the freezing compartment). This segmentation allows accurate temperature measurement at multiple points without requiring a single complex sensing system, resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The refrigerator processor calculates the load accumulation amount in advance based on temperature variations before triggering the load correspondence operation. This preliminary calculation of load accumulation allows the system to determine the optimal timing for load correspondence operation, improving timing accuracy without adding significant system complexity
2Measurement precision
If multiple temperature sensors are used to improve temperature measurement accuracy, then temperature variation estimation becomes more accurate, but the device complexity increases
Solution Approach 1:
The temperature sensors serve multiple functions: they monitor compartment temperatures, calculate load accumulation amounts, and trigger load correspondence operations. This multi-functionality allows accurate temperature variation estimation using the same sensor system without adding separate dedicated sensors, thus improving measurement precision while limiting the increase in device complexity
Solution Approach 2:
The refrigerator processor continuously monitors temperature variations from the temperature sensors and uses this feedback to calculate load accumulation amounts and determine when to perform load correspondence operations. This feedback mechanism improves temperature variation estimation accuracy by dynamically adjusting operations based on actual temperature changes rather than relying on fixed thresholds
3Productivity
If load correspondence operation is delayed until temperature reaches a predetermined level, then the control logic is simple, but energy efficiency is reduced due to delayed response
Solution Approach 1:
The system calculates the load accumulation amount in advance based on temperature variations before the temperature reaches the predetermined threshold. This preliminary calculation allows the refrigerator to anticipate when load correspondence operation should occur, improving response speed and energy efficiency by avoiding delayed responses while keeping the control logic relatively simple
Solution Approach 2:
The patent replaces the conventional mechanical threshold-based trigger system with an intelligent calculation system that uses temperature variation data to estimate load accumulation. This substitution allows the system to determine the optimal timing for load correspondence operation more accurately, improving both response speed and energy efficiency without requiring complex additional hardware
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
Enhances energy efficiency and system stability by accurately estimating temperature variations and performing load correspondence operations, reducing power consumption and improving operational efficiency.
Implementation Method 1
one or more first temperature sensor that senses refrigerating compartment-internal temperature in a refrigerating compartment of the refrigerator; one or more second temperature sensor that senses freezing compartment-internal temperature in a freezing compartment of the refrigerator
Implementation Method 2
A refrigerator is operated by driving of a compressor disposed therein. Cold air that is supplied into a refrigerator is generated by a heat exchange process of a refrigerant and is continuously supplied into the refrigerator through a repeatedly performed cycle of compression-condensation-expansion-evaporation
Implementation Method 3
Cold air that is supplied into a refrigerator is generated by a heat exchange process of a refrigerant
Implementation Method 4
the supplied refrigerant uniformly transfers in the refrigerator by convection, whereby food is kept at a desired temperature in the refrigerator
Implementation Method 5
a first evaporating unit that diverges from the condensing unit and is connected to an intake side of the first compressing unit positioned upstream in the flow direction of the refrigerant; a second evaporating unit that diverges from the condensing unit together with the first evaporating unit
Data Source
AI summary
An artificial intelligent refrigerator is disclosed. The artificial intelligent refrigerator includes: one or more first temperature sensor that senses refrigerating compartment-internal temperature in a refrigerating compartment of the refrigerator; one or more second temperature sensor that senses freezing compartment-internal temperature in a freezing compartment of the refrigerator; and a refrigerator processor that calculates a load accumulation amount for food put in the refrigerator on the basis of the refrigerating compartment-internal temperature or the freezing compartment-internal temperature, and performs a load correspondence operation using the calculated load accumulation amount. According to the artificial intelligent refrigerator of the present disclosure, one or more of a user terminal, and a server of the present disclosure may be associated with an artificial intelligence module, a drone ((Unmanned Aerial Vehicle, UAV), a robot, an AR (Augmented Reality) device, a VR (Virtual Reality) device, a device associated with 5G services, etc.