Intelligent Thermostat Schedule Learning for Energy-Saving Comfort Control
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Solution Overview
Problem
Existing HVAC thermostats either lack user-friendly interfaces, leading to missed energy-saving opportunities or intimidate users with complex settings, resulting in suboptimal energy usage, and existing solutions either rely heavily on user input or fail to generate efficient energy-saving schedules.
Innovation Solution
A thermostat with a ring-shaped user interface and processing system that automatically adjusts setpoint temperatures based on user input and ambient conditions, generating a schedule that balances energy efficiency and user comfort by resetting temperatures after predetermined intervals and learning from user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If programmable thermostats with multiple settings are provided, then energy-saving capability is improved, but device complexity increases making users intimidated
Solution Approach 1:
The thermostat automatically performs scheduling functions without requiring extensive user programming. The system self-adjusts temperatures based on learned patterns and user preferences, eliminating the need for complex manual programming while maintaining energy-saving capabilities
Solution Approach 2:
The system dynamically changes temperature parameters based on time of day, day of week, and learned user preferences. Instead of requiring users to set fixed parameters, the thermostat automatically adjusts temperature profiles, simplifying the interface while optimizing energy savings
2Loss of energy
If programmable thermostats with multiple settings are provided, then energy-saving capability is improved, but ease of operation deteriorates
Solution Approach 1:
The thermostat performs automatic scheduling and temperature adjustment without requiring users to navigate complex programming interfaces. The system learns user patterns and automatically implements energy-saving schedules, making advanced features accessible to all users
Solution Approach 2:
The system pre-configures temperature schedules based on typical usage patterns and user preferences before peak energy consumption periods. This preliminary setup eliminates the need for users to manually program schedules at the moment of need
3Adaptability or versatility
If interview-based programming is used, then adaptability is improved, but reliability deteriorates due to user errors
Solution Approach 1:
The thermostat continuously monitors user manual adjustments and uses this feedback to refine and update schedules automatically. This closed-loop learning system adapts to user preferences over time without relying on potentially erroneous initial user input
Solution Approach 2:
The system automatically generates and refines schedules based on observed user behavior patterns rather than relying on user-provided information. The thermostat serves itself by learning from actual usage data, eliminating reliability issues associated with user input accuracy
4Ease of operation
If manufacturer default profiles are used, then ease of operation is improved, but energy-saving capability deteriorates
Solution Approach 1:
The thermostat implements manufacturer defaults immediately for ease of operation, then continuously learns and adapts the schedule over time based on observed user patterns, progressively optimizing energy savings without requiring user intervention
Solution Approach 2:
The system transitions from static manufacturer default profiles to dynamic, learned schedules that adapt continuously based on user behavior. This dynamic evolution maintains simplicity of operation while progressively improving energy-saving efficiency
Data Source
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Figure 3A~3B
Figure 4A~4C
AI summary
A user-friendly programmable thermostat is described that includes receiving an immediate-control input to change set point temperature, controlling temperature according to the set point temperature for a predetermined time interval, and then automatically resetting the set point temperature upon the ending of the predetermined time interval such that the user is urged to make further immediate-control inputs. A schedule for the programmable thermostat is automatically generated based on the immediate-control inputs. Methods are also described for receiving user input relating to the user's preference regarding automatically generating a schedule, and determining whether or not to automatically adopt an automatically generated schedule based on the received user input.