Air conditioner, air conditioner control method, and air conditioner control system
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Solution Overview
Problem
Existing air conditioner control systems fail to prevent overcooling by adjusting the set temperature before discomfort occurs, leading to increased uncomfortable time and energy waste.
Innovation Solution
An air conditioner system utilizing AI models to predict and adjust the set temperature and fan speed by communicating with a server device to prevent overcooling, incorporating a communication interface, memory, and processor to execute instructions for temperature and fan speed adjustments based on AI models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If the air conditioner maintains a low set temperature to ensure user comfort, then user comfort is improved, but energy consumption increases and overcooling occurs
Solution Approach 1:
The system performs preliminary action by predicting future temperature trends using AI models before overcooling actually occurs. The server device receives current state information, generates predicted temperature graphs using a second AI model, and proactively sends set temperature increase requests to prevent overcooling discomfort before it happens, thereby reducing energy waste from unnecessary low-temperature operation
Solution Approach 2:
The system implements feedback by continuously monitoring current state information (operation time, set temperature, indoor temperature) and using AI models to generate predicted temperature graphs. The server compares these predictions with comfortable temperature graphs from a first AI model, and adjusts the set temperature based on this feedback loop to prevent overcooling while optimizing energy consumption
2Object-affected harmful factors
If the air conditioner adjusts set temperature frequently to prevent overcooling, then overcooling prevention is improved, but system complexity increases
Solution Approach 1:
The system uses an intermediary approach by introducing a server device that handles the complex AI model computations and decision-making logic. The air conditioner itself remains relatively simple, transmitting current state information to the server and executing set temperature adjustments based on server instructions. This intermediary server manages the complexity of multiple AI models and prediction algorithms without burdening the air conditioner hardware
Solution Approach 2:
The system replaces complex mechanical control logic with AI-based predictive modeling. Instead of using traditional rule-based temperature adjustment mechanisms, the system employs machine learning models (first AI model for comfortable temperature, second AI model for predicted temperature) to automatically determine optimal set temperature adjustments, reducing the need for complex mechanical sensors and control circuits
Data Source
AI summary
An air conditioner includes a communication interface to communicate with a server device, a memory to store one or more instructions, and at least one processor configured to execute the stored one or more instructions to transmit, to the server device through the communication interface, current state information including one or more of operation time information of the air conditioner, set temperature information of the air conditioner, and current indoor temperature information, receive a set temperature increase request corresponding to the transmitted current state information from the server device through the communication interface, and adjust a set temperature of the air conditioner based on the received set temperature increase request, and the set temperature increase request is received when an overcooling period is identified.