Air conditioning apparatus
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional air conditioning apparatuses require manual user input to control temperature and humidity, and cannot predict future changes in occupancy, leading to inefficient energy usage and comfort issues.
Innovation Solution
An air conditioning apparatus equipped with sensors to collect environmental data, including temperature, humidity, and occupancy, uses a learning model to predict future loads and adjust operation modes and intensities automatically based on classified information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual user input is required to control air conditioning apparatus, then user can directly control temperature and humidity, but user convenience deteriorates and operation complexity increases
Solution Approach 1:
The air conditioning apparatus automatically collects environmental information through sensors, classifies occupancy patterns, predicts future loads using learning models, and adjusts operation modes without requiring manual user input. The system serves itself by making intelligent decisions based on collected data, eliminating the need for continuous user interaction while maintaining comfortable indoor conditions
Solution Approach 2:
The system continuously collects environmental information through sensors, processes this data through classification and prediction algorithms, and uses the results to automatically adjust operation modes. This closed-loop feedback mechanism enables the apparatus to adapt to changing conditions automatically, improving user convenience while maintaining precise temperature and humidity control
2Productivity
If conventional air conditioning apparatus determines operation state based on current temperature only, then control is simple, but it cannot predict future occupancy changes leading to energy waste
Solution Approach 1:
The system performs preliminary actions by predicting future occupancy loads using historical environmental data and machine learning models. Based on these predictions, the air conditioning apparatus pre-adjusts operation modes and output intensities before occupancy changes occur, optimizing energy efficiency while maintaining comfortable conditions. This proactive approach allows the system to prepare for upcoming changes rather than merely reacting to current conditions
Solution Approach 2:
The system dynamically changes operational parameters including operation mode (cooling, heating, ventilation) and output intensity based on predicted occupancy loads. By continuously adjusting these parameters according to forecasted conditions rather than fixed temperature thresholds, the apparatus optimizes energy consumption while adapting to future environmental changes
3Temperature
If output intensity is increased to maintain target temperature when number of persons increases, then target temperature is maintained, but energy consumption increases
Solution Approach 1:
The system predicts future occupancy changes using historical environmental information and machine learning models. When an increase in occupancy is predicted, the air conditioning apparatus pre-adjusts the output intensity to the appropriate level before the occupancy change occurs. This preliminary adjustment prevents temperature fluctuations while avoiding the energy waste associated with reactive intensity increases
Solution Approach 2:
The system continuously monitors environmental parameters including temperature, humidity, and occupancy indicators. This feedback is processed through classification and prediction algorithms that determine the optimal operation mode and output intensity. By basing control decisions on predicted occupancy rather than merely current temperature deviations, the system maintains target temperature while optimizing energy consumption patterns
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Disclosed are an air conditioning apparatus and a control method thereof. An air conditioning apparatus comprises: a driving unit for performing a pre-configured function of the air conditioning apparatus; a sensor for collecting environmental information around the air conditioning apparatus; a memory for storing the collected environmental information; and a processor for controlling an operation of the driving unit on the basis of schedule information including an operating state defined according to a time change, and modifying the schedule information on the basis of environmental information collected during a pre-configured period of time.