Appliance Scheduling Using User Location and Sensor Feedback
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Solution Overview
Problem
Existing appliance management systems fail to synchronize appliances with a user's schedule, leading to inefficient energy usage and increased energy consumption, as they do not consider the user's presence or schedule when optimizing operations.
Innovation Solution
A system that uses sensor data and user location information to dynamically modify appliance features, such as cycle duration or completion times, to align with the user's schedule, even if it requires more energy, ensuring appliances operate according to the user's preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If appliances operate according to optimized energy usage patterns, then energy consumption is reduced, but user convenience and satisfaction deteriorate as appliances may not be ready when users return
Solution Approach 1:
The system dynamically adjusts appliance operation schedules based on real-time user location data and historical patterns. Instead of fixed energy optimization schedules, the system adapts timing to match when users are actually present or expected to return, allowing energy-saving modes to be applied only when they don't conflict with user needs
Solution Approach 2:
The system continuously monitors user location via GPS tracking and appliance status, then uses this feedback to adjust operation schedules. When users are detected to be away longer than expected, the system modifies appliance timing accordingly, creating a closed-loop system that balances energy efficiency with user convenience based on actual behavior patterns
2Productivity
If appliances are synchronized to finish cycles at standard times, then energy usage patterns are predictable and optimized, but the system lacks adaptability to individual user schedules and preferences
Solution Approach 1:
The system performs preliminary actions by pre-scheduling appliance operations based on historical user patterns and expected availability. It proactively adjusts cycles to complete before users return home, rather than waiting for users to manually check or adjust settings, thus maintaining energy efficiency while adapting to individual schedules
Solution Approach 2:
The system changes operational parameters such as cycle duration, start time, and completion timing based on user-specific data. Each user's appliance schedules are customized by modifying standard parameters to match their work hours, travel patterns, and preferred availability, enabling both optimization and adaptability
3Ease of operation
If dryer cycles are extended to match user availability, then user convenience is improved, but energy consumption and operation time increase
Solution Approach 1:
The system uses periodic checking of user location and appliance status to determine optimal cycle timing. Instead of continuously running appliances or waiting idle, it employs periodic monitoring and batched operation adjustments, running cycles in optimized periods that balance user needs with energy efficiency based on detected availability patterns
Data Source
AI summary
A method and system are provided that synchronize one or more appliances to one or more users' schedules. Sensor data may be obtained from a sensor. The sensor data may indicate a state of a first appliance. A user location may be determined. A first characteristic of the first appliance may be obtained. Based upon the user location and the sensor data, a schedule indicating when the user will desire a state change of the first appliance may be determined. A feature of the first appliance may be dynamically modified to cause the first appliance to operate according to the schedule. A notice may be sent to the user that contains information about the first appliance.