Energy efficiency promoting schedule learning algorithms for intelligent thermostat
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing HVAC thermostats either lack user-friendly interfaces, leading to missed energy-saving opportunities, or overwhelm users with complex settings that are not optimally utilized, creating a tension between energy-saving sophistication and practical application in residential and commercial settings.
Innovation Solution
A thermostat with a ring-shaped user interface and processing system that automatically adjusts temperature settings based on user input, generates schedules, and provides notifications, allowing for intuitive control and energy-efficient operation.
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 user interface complexity increases making it difficult for typical users to access and utilize features
Solution Approach 1:
The thermostat automatically performs scheduling functions without requiring user programming. The system observes user manual temperature adjustments and autonomously generates optimized schedules, eliminating the need for users to navigate complex programming interfaces while still achieving energy-saving goals through automated behavior learning and implementation
2Ease of operation
If manufacturer default profiles are used, then ease of operation is improved, but energy-saving effectiveness deteriorates due to one-size-fits-all approach
Solution Approach 1:
The thermostat dynamically adapts to individual user behavior patterns rather than using static manufacturer defaults. The system continuously observes manual temperature adjustments and automatically generates customized schedules specific to each household's needs, transforming the rigid one-size-fits-all approach into a flexible, personalized energy management system that maintains ease of use while improving energy-saving effectiveness
Solution Approach 2:
The system incorporates feedback loops where the thermostat monitors user manual adjustments and uses this information to refine and optimize scheduling decisions. By continuously learning from user behavior patterns and automatically adjusting schedules accordingly, the system closes the gap between default profiles and personalized optimization without requiring user intervention
3Ease of operation
If simple non-programmable thermostats are used, then ease of operation is improved, but energy-saving opportunities are lost due to lack of automated control
Solution Approach 1:
The thermostat autonomously captures and implements energy-saving opportunities by observing user behavior patterns and automatically generating optimized schedules. The system performs the energy-saving control functions that would otherwise require complex user programming, maintaining the simplicity of non-programmable thermostats while enabling automated energy conservation through self-learning and self-implementation capabilities
Data Source
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.