AI Smart Plug Control for Priority-Based Energy Saving
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Solution Overview
Problem
Current smart home systems lack the capability to fully automate energy management, failing to maximize energy efficiency in homes and offices despite the growing popularity of IoT devices.
Innovation Solution
An AI-powered IoT system that collects power usage information from various devices, determines priority levels using machine learning models, and transmits control signals to manage power consumption based on pre-configured priorities and power management signals, including entering or exiting power-saving modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If smart home systems use passive control based on user input or configuration, then ease of operation is improved, but energy efficiency is not maximized
Solution Approach 1:
The system enables devices to automatically manage their own power consumption by analyzing usage patterns and making intelligent decisions about when to power devices on or off, eliminating the need for constant user intervention while maximizing energy efficiency
Solution Approach 2:
The system continuously monitors power consumption data from smart plugs and uses this feedback to dynamically adjust device power states, creating a closed-loop control system that optimizes energy usage based on actual usage patterns rather than static user configurations
2Loss of energy
If the system monitors and controls all smart devices actively, then energy efficiency is improved, but device complexity increases
Solution Approach 1:
The system divides the smart home into independent controllable units by using smart plugs as individual monitoring and control points for each device, allowing granular power management without requiring complex integration across the entire system
Solution Approach 2:
The smart plug acts as an intermediary device between the power source and the connected device, handling all monitoring and control functions at the plug level rather than requiring complex coordination between multiple system components
Data Source
AI summary
AI-assisted Connected Home systems for improving power efficiency at homes and offices are described. The system may perform operations including: receiving, from each of a plurality of power receptacles, power usage information of an electrical device attached to the power receptacle; determining, for each of the plurality of power receptacles, a plurality of power usage metrics of the power receptacle based on the power usage information; feeding the plurality of power usage metrics into a machine learning model to obtain a priority of the electrical device attached to the power receptacle, wherein the priority is one of a plurality of pre-configured priorities; obtaining a power management signal; and transmitting a plurality of control signals to the plurality of power receptacles based on the power management signal and respective priorities of the plurality of electrical devices attached to the plurality of power receptacles.