Air conditioner with multiple setting pattern operation
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Solution Overview
Problem
Conventional air conditioners using Predicted Mean Vote (PMV) control methods struggle to provide individual comfort as user preferences vary significantly, even in the same environment, leading to limitations in collective user comfort.
Innovation Solution
An air conditioner system incorporating a machine learning model that adjusts settings based on user feedback and environment information, using a main setting pattern and a sub-setting pattern generated by a server, which considers user presence and environmental conditions to optimize comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If PMV-based control is used to operate the air conditioner based on average comfort conditions, then the system can be operated with simple control logic, but the air conditioner cannot provide individualized comfort for different users with varying preferences
Solution Approach 1:
The patent segments the control system into multiple components: a server that stores and manages multiple user preference profiles, a database for storing environment-information and preference-data, and a controller that selects and applies appropriate profiles. This segmentation allows individualized comfort adaptation without overwhelming complexity in a single device, as each component has a specialized function.
Solution Approach 2:
The patent introduces a server as an intermediary between the user and the air conditioner controller. The server acts as a mediator that receives environment information, queries the database for appropriate preference profiles, and returns control commands to the air conditioner. This intermediary approach distributes complexity across the network infrastructure rather than concentrating it in the air conditioner itself.
2Adaptability or versatility
If the air conditioner operates based on average comfort conditions for all users, then the control logic remains simple, but the system fails to account for individual user preferences that vary even in the same environment
Solution Approach 1:
The patent implements preliminary action by pre-storing multiple user preference profiles in the database before actual operation. Each profile contains pre-defined comfort parameters (temperature, humidity, airflow) for different users. When the air conditioner operates, the system simply retrieves and applies the appropriate pre-stored profile rather than calculating optimal settings in real-time, thus preserving user preference information while maintaining simple control logic.
Solution Approach 2:
The system employs feedback mechanisms where the controller receives environment information from sensors, compares current conditions with stored preference profiles, and adjusts operations accordingly. The server also receives operation results and can update the database with new preference data, creating a continuous feedback loop that preserves and refines user preference information over time.
3Adaptability or versatility
If multiple user profiles and environment information are processed in real-time, then individualized comfort can be achieved, but the system complexity and computational requirements increase significantly
Solution Approach 1:
The patent segments the automated control process into distinct stages: environment information acquisition by sensors, data transmission to the server, profile matching and selection by the server's processor, and control command execution by the air conditioner controller. This segmentation of automated tasks distributes computational requirements across multiple devices, reducing the automation burden on any single component while maintaining high adaptability.
Solution Approach 2:
The server acts as an intermediary that handles the complex computational tasks of processing environment information and matching user profiles. By offloading these automated decision-making processes to the server, the air conditioner itself can maintain simpler automation logic, merely executing commands received from the server based on pre-processed environmental data.
Data Source
AI summary
Disclosed are an air conditioner, an air conditioning system, and a control method thereof. The air conditioner includes an input interface, a communication interface configured to communicate with a server, and a processor configured to receive a main setting pattern from the server and operate according to the received main setting pattern, based on a setting value changing, transmit the changed setting value and first environment information at the time when the setting value is changed to the server, based on receiving a selection of an artificial intelligence control operation from a user, transmit current second environment information to the server, control the communication interface to receive the main setting pattern or a sub-setting pattern corresponding to the changed setting value from the server based on the first environment information and the second environment information, and operate according to the received main setting pattern or the received sub-setting pattern.