Agent Apparatus Relays Control Signals to Simplify Home Network Operations
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Solution Overview
Problem
Users face inconvenience when operating multiple electrical devices in a home network, as they need to manually select and control each device using multiple remote controllers, leading to complex and time-consuming settings, especially for those unfamiliar with the devices.
Innovation Solution
An agent apparatus that collects, stores, and learns user and environment information to generate and output macro lists, allowing for simplified operation of multiple electrical devices by relaying control signals and automating device control sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a universal remote controller is used to control multiple electrical apparatuses, then the number of remote controllers is reduced, but the complexity of operation increases and users need to manually select each device and function
Solution Approach 1:
The agent apparatus automatically identifies users based on collected information (such as voice recognition, face recognition, or input data) and autonomously determines and executes the appropriate control operations for electrical apparatuses. This eliminates the need for users to manually select devices and functions, as the system serves itself by making intelligent decisions based on user identity and environmental context.
Solution Approach 2:
The agent apparatus acts as an intermediary between the user and multiple electrical apparatuses. Instead of the user directly controlling each device, the agent receives user input, processes it through learned patterns and environmental data, and translates it into appropriate control signals for the target devices. This mediator role simplifies user interaction while maintaining precise device control.
2Reliability
If manual control of each electrical apparatus is required, then precise device control is achieved, but the time and effort required for operation increases
Solution Approach 1:
The agent apparatus performs preliminary actions by collecting and analyzing user information, environment information, and operation control information in advance. It learns user preferences and typical operation patterns beforehand, so when a user wants to control devices, the system has already prepared the appropriate control sequences. This preliminary preparation significantly reduces the time required for actual device operation while maintaining precise control.
Solution Approach 2:
The system implements feedback mechanisms where operation results and environmental changes are continuously monitored. The agent learns from past operations and environmental conditions, adjusting future control actions to optimize both precision and speed. This feedback loop enables the system to refine its control strategies over time, achieving reliable device control with minimal user intervention time.
3Adaptability or versatility
If operation control information is collected and stored for each user, then customized control is enabled, but the complexity of information management increases
Solution Approach 1:
The agent apparatus implements a universal information management system that handles multiple types of data (user identification, environment information, operation patterns, device states) through a single integrated framework. This multi-functional system can process and correlate different information types simultaneously, enabling user customization without requiring separate management systems for each data type. The universal approach reduces overall complexity despite the diverse information being managed.
Solution Approach 2:
The system merges multiple information streams (user identity data, environmental sensors, operation history, device status) into a unified context model. By combining these previously separate information types into a single integrated representation, the system simplifies information management while enabling comprehensive user customization. The merged information structure allows the agent to make holistic decisions based on all available data without managing each data type separately.
Data Source
AI summary
A display apparatus including a display which displays content, a communicator configured to communicate with a remote controller and an external device, and a controller. The controller being configured to, upon receiving a control command from the external device, control operation of the display apparatus based on the received control command, control the received control command to be transmitted to the remote controller, and control the communicator to transmit the received control command to the external device through the remote controller.