Appliance State Recognition Using Multi-Sensor User Behavior Modeling
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Solution Overview
Problem
Legacy and some smart appliances lack functionality for monitoring and optimizing user interaction, leading to inefficient usage and potential issues like forgotten laundry transfers and moldy clothes, due to limited prediction of user behavior and interaction.
Innovation Solution
An appliance state recognition apparatus that uses sensor data from temperature, motion, and contact sensors to determine appliance states and generate responses, such as delayed start times or user notifications, to optimize appliance usage and user interaction, incorporating behavior modeling and crowd-sourced information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If legacy appliances are used without smart monitoring functionality, then device complexity is reduced, but user interaction efficiency and appliance usage optimization deteriorate
Solution Approach 1:
A separate monitoring device with sensors and processing capabilities is introduced as an intermediary between the appliance and the user. This external device attaches to the appliance and handles all complex monitoring, state recognition, and optimization functions, allowing the appliance itself to remain simple while gaining smart functionality through the intermediary system.
Solution Approach 2:
The monitoring device autonomously recognizes appliance states, predicts user behavior, and determines optimal operation times without requiring continuous user input or intervention. The system serves itself by automatically adjusting appliance operation based on sensor data and learned patterns, freeing the user from manual monitoring and optimization tasks.
2Productivity
If smart appliances with behavior prediction are deployed, then appliance usage optimization is improved, but loss of time for data processing and state recognition increases
Solution Approach 1:
The system performs preliminary data collection and processing by continuously monitoring appliance states and storing sensor data for later analysis. User behavior patterns are learned in advance through crowd-sourced information and historical data, enabling rapid state recognition and optimization decisions without time-consuming processing during critical operations.
Solution Approach 2:
The system implements continuous feedback loops where sensor data from appliance operation is immediately processed and used to adjust subsequent operations. Real-time feedback from temperature, motion, and contact sensors enables the system to rapidly recognize states and make optimization decisions, minimizing processing delays while maintaining high productivity.
3Measurement precision
If multiple sensors are used for state recognition, then measurement precision of appliance states is improved, but device complexity increases
Solution Approach 1:
The monitoring system is segmented into multiple independent sensor modules, each responsible for detecting specific appliance states (temperature, motion, contact). This segmentation allows each sensor to be optimized for its specific function while the central processing unit integrates their data, achieving high measurement precision without requiring a single complex sensor system.
Solution Approach 2:
A single monitoring device integrates multiple sensor types (temperature, motion, contact sensors) into one universal system that can detect various appliance states. This multi-functional approach achieves comprehensive state recognition precision while reducing overall system complexity compared to using separate dedicated devices for each sensor type.
Data Source
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AI summary
Embodiments herein relate to recognition of an appliance state based on sensor data and determination of a response based at least in part on the appliance state. In various embodiments, an apparatus to recognize an appliance state may include a sensor data module to identify sensor data in one or more signals relating to data from one or more sensors associated with an appliance, an appliance state recognition module to determine an appliance state of the appliance based at least in part on the sensor data, a response module to determine a response based at least in part on the appliance state, and a transmission module to send the response to at least one of an appliance controller for the appliance or a presentation device. Other embodiments may be described and/or claimed.