Electronic device and method for controlling same
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Solution Overview
Problem
Existing devices that use water or perform moisture-related operations, such as dishwashers or dryers, are influenced by varying temperature and humidity conditions, making it difficult to determine optimal driving times and methods without accurate environmental data.
Innovation Solution
An electronic device that predicts humidity using a model trained on temperature and humidity information from multiple peripheral devices and an external server, allowing it to determine the optimal operation time and method for target devices based on humidity prediction information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If temperature and humidity are obtained directly from a single device's sensor, then the measurement is simple and quick, but the accuracy is insufficient due to local environmental variations
Solution Approach 1:
The patent combines temperature and humidity sensors from multiple peripheral devices (first, second, and third devices) to obtain comprehensive environmental data. By merging the sensing capabilities of multiple devices, the system achieves more accurate representation of the overall environmental conditions while managing complexity through coordinated data collection protocols.
Solution Approach 2:
The control device serves multiple functions: it collects environmental data from multiple sources, performs AI-based predictions, determines optimal driving parameters, and coordinates multiple peripheral devices. This multi-functionality allows a single system to handle the complexity of multi-device coordination while providing comprehensive environmental monitoring and control.
2Measurement precision
If driving time and method are determined based on real-time sensor data only, then the response is immediate, but the accuracy is insufficient due to lack of historical context
Solution Approach 1:
The system performs preliminary data collection from multiple peripheral devices and pre-processes this information using an AI model before the actual control decision is needed. By preparing environmental assessments in advance based on historical and real-time data, the system reduces processing time during critical decision moments while maintaining high accuracy through comprehensive data analysis.
Solution Approach 2:
The system incorporates feedback loops where driving history information from multiple devices is continuously fed into the AI model, which then refines its predictions. This feedback mechanism allows the system to learn from past performance and improve future predictions, balancing the need for rapid response with the benefit of accumulated knowledge.
3Productivity
If a single device determines driving parameters, then the control is simple, but the optimization is insufficient due to lack of coordinated environmental data
Solution Approach 1:
The system segments the environmental monitoring function across multiple independent peripheral devices, each contributing its local sensor data. This segmentation allows each device to maintain simple individual operation while the control device integrates their data to achieve comprehensive environmental awareness, optimizing driving parameters based on the combined information without requiring complex inter-device coordination.
Solution Approach 2:
The control device acts as an intermediary that receives environmental data from multiple peripheral devices, processes this information through AI predictions, and determines optimal driving parameters. This intermediary role centralizes the coordination complexity in a single device, allowing peripheral devices to remain simple while still benefiting from optimized control decisions based on comprehensive environmental data.
Data Source
AI summary
An electronic device and a method for controlling same. The electronic device comprises a communication interface; a memory; and one or more processors. The one or more processors receive temperature and humidity information and operation history of a plurality of peripheral devices through a communication interface; based on a driving signal of a target device is received through the communication interface, input the temperature and humidity information and the information about the operation history of the plurality of peripheral devices into a humidity prediction model and identify a vector value output from the humidity prediction model; identify humidity prediction information for a space in which the target device is located on the basis of the identified vector value; and transmit driving information, according to which the target device is to be operated based on the driving signal, corresponding to the identified humidity prediction information to the target device.