Smart Plug Server for Home Appliance Power Optimization
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Solution Overview
Problem
Existing home appliance control systems, particularly those using IoT devices and smart plugs, lack the ability to dynamically adjust power usage based on user patterns and are not effectively communicatively connected to mobile terminals, limiting their intelligence and usability.
Innovation Solution
A method and apparatus that utilize a mobile terminal connected to smart plugs to collect and analyze power usage data, generate optimal usage settings through deep learning models, and control power distribution to home appliances, enabling intelligent management and reducing energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing smart plugs are used to control home appliances, then power supply management is provided, but the interface is limited and passive without analyzing users' life patterns
Solution Approach 1:
A server acts as an intermediary between smart plugs and mobile terminals, collecting power usage data from multiple smart plugs, analyzing user life patterns, and providing intelligent control recommendations. This mediator enables pattern analysis without requiring complex processing in each smart plug device.
Solution Approach 2:
The system automatically analyzes power usage data and user patterns without requiring manual user input or configuration. The smart plugs autonomously report their data to the server, which then self-service generates usage patterns and provides control recommendations.
2Loss of information
If home appliances operate upon receiving user inputs, then basic control function is provided, but no function of analyzing users' life patterns is available
Solution Approach 1:
The server serves as an intermediary that collects power usage data from multiple smart plugs, processes this data to extract user life patterns, and stores these patterns for future reference. This centralizes the complex data processing task.
Solution Approach 2:
The system pre-analyzes power usage data to generate usage patterns in advance, so that when control decisions are needed, the pattern information is already available. This preliminary analysis enables faster, more intelligent response to user needs.
3Ease of operation
If home appliances are not communicatively connected to mobile terminals, then simple operation is maintained, but intelligent management is difficult
Solution Approach 1:
The server acts as an intermediary that bridges mobile terminals and smart plugs, enabling intelligent management functions while keeping the smart plugs themselves simple. The server handles complex communication and data processing, allowing mobile terminals to provide intelligent control without complicating the appliance-side devices.
4Productivity
If power usage data is collected and analyzed, then optimal usage settings can be generated, but data processing requirements increase
Solution Approach 1:
The server acts as an intermediary that centralizes data processing tasks, allowing mobile terminals and smart plugs to remain energy-efficient while still enabling comprehensive power usage analysis. The server handles the computationally intensive pattern recognition and optimization calculations.
Data Source
AI summary
An intelligent home appliance control method includes obtaining power usage data of a device provided with power, generates information related to an optimal usage setting for the device, and controlling power provided to the device, thereby minimizing power usage required for using multiple home appliances at home. At least one of the home appliance control apparatus, an intelligent computing device, a terminal, a server, and an IoT device may be associated with an artificial intelligence (AI) module, a drone (an unmanned aerial vehicle (UAV)), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to a 5G service, or the like.