AI-Learned Sleep Cooling Control for Air Conditioner Timing
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Solution Overview
Problem
Users face inconvenience in manually switching an air conditioning apparatus from a general cooling mode to a sleep cooling mode and vice versa, as existing systems require manual input that often does not align with their actual sleep patterns.
Innovation Solution
An air conditioning apparatus and method that utilizes user sleep information, obtained through an external server using an AI model like TBATS, to automatically operate in a sleep cooling mode without user manipulation, based on periodic sleep patterns and usage history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual input is required to switch between general cooling mode and sleep cooling mode, then the air conditioning apparatus can operate in sleep cooling mode, but user convenience deteriorates due to the need for repeated manual operations
Solution Approach 1:
The air conditioning apparatus automatically learns and detects user sleep patterns without external intervention. The system self-adjusts by analyzing usage history data to determine when the user typically enters sleep mode, eliminating the need for manual input commands while maintaining operational accuracy
Solution Approach 2:
The system continuously monitors and analyzes usage history data to detect periodic patterns in user behavior. By processing this feedback information, the air conditioning apparatus adapts its operation to automatically switch between general cooling mode and sleep cooling mode based on detected sleep patterns, creating a closed-loop control system
2Extent of automation
If on/off time is input in advance for automatic operation, then automation is achieved, but reliability deteriorates due to inconsistency with actual user sleep patterns
Solution Approach 1:
The system autonomously learns user sleep patterns by analyzing usage history data without requiring pre-programmed schedules. The air conditioning apparatus self-adjusts its automatic operation timing based on detected periodic patterns, ensuring reliability by adapting to actual user behavior rather than relying on fixed predetermined times
Solution Approach 2:
The automatic operation timing is dynamic rather than static. The system continuously detects and adapts to changes in user sleep patterns by processing usage history data, allowing the automatic on/off times to evolve and remain aligned with actual user behavior patterns
3Measurement precision
If usage history data is collected and processed to detect sleep patterns, then automatic operation accuracy improves, but device complexity increases due to data processing requirements
Solution Approach 1:
The processor acts as an intermediary that collects usage history data and processes it to detect sleep patterns. By centralizing the data processing function in the processor, the system achieves accurate sleep pattern detection without distributing complex processing logic across multiple components, thereby managing device complexity effectively
Data Source
AI summary
The present disclosure provides an air conditioning apparatus and a method for controlling same. The method for controlling an air conditioning apparatus comprises the steps of: the air conditioning apparatus receiving, from an external server, user sleep information acquired on the basis of data on time for which the air conditioning apparatus is operated in a sleep cooling mode used during the user's sleep; and operating in the cooling mode on the basis of the user sleep information. Specifically, at least part of an operation for acquiring the user sleep information on the basis of the user's control command may use an artificial intelligence model obtained by learning according to at least one of a machine learning, a neural network, and a deep learning algorithm.