Occupant Feedback Aggregation for Adaptive Building Temperature Control
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Solution Overview
Problem
Existing methods for collecting and aggregating group preferences are costly and inefficient, leading to over-cooling or over-heating in buildings due to the difficulty in obtaining and analyzing individual preferences for environmental settings like temperature, which results in wasted energy and discomfort for occupants.
Innovation Solution
A system comprising feedback devices that allow individuals to provide preference feedback in real-time with low transaction costs, using a computer to collect and aggregate data to construct a group preference model that predicts future preferences and adjusts environmental settings accordingly, optimizing energy usage and comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional survey methods are used to collect individual preferences, then preference information can be obtained, but the transaction costs are high and the process is inefficient
Solution Approach 1:
The system enables individuals to automatically provide preference feedback through simple actions (like button presses or digital inputs) without requiring manual survey completion. The feedback mechanism is integrated into the environment itself, allowing users to self-report preferences effortlessly, thereby reducing both time and transaction costs while maintaining information quality.
Solution Approach 2:
The patent replaces traditional mechanical survey collection methods (paper forms, manual data entry) with electronic and automated feedback systems. Digital sensors, buttons, and computer-based interfaces substitute for manual processes, enabling rapid data collection and automatic aggregation of preferences without the high transaction costs associated with traditional methods.
2Ease of operation
If building temperature is preset to a single value, then system operation is simple, but occupant comfort is compromised and energy is wasted
Solution Approach 1:
The system transitions from a static, fixed temperature preset to a dynamic adjustment mechanism that continuously adapts to changing occupant preferences. The building management system automatically modifies temperature settings based on real-time feedback from occupants, allowing the operation to remain simple while significantly reducing energy waste through optimized climate control.
Solution Approach 2:
The patent implements a closed-loop feedback system where occupant preferences are continuously collected and used to adjust building environmental settings. This feedback mechanism enables the system to automatically optimize temperature and other environmental parameters, maintaining ease of operation while eliminating the energy waste associated with fixed, one-size-fits-all presets.
3Ease of operation
If building temperature is preset to a single value, then system operation is simple, but occupant satisfaction is reduced
Solution Approach 1:
The system evolves from a static temperature preset to a dynamic adjustment mechanism that adapts to varying occupant needs throughout the day and across different seasons. This dynamic approach maintains operational simplicity while significantly improving occupant satisfaction by responding to changing environmental preferences.
Solution Approach 2:
The patent establishes a feedback loop where occupant preferences are systematically collected and translated into automated environmental adjustments. This feedback-driven approach allows the system to maintain simple operation while reliably improving occupant satisfaction by continuously aligning environmental conditions with actual user preferences.
4Device complexity
If individual preferences are not aggregated, then data collection is simple, but group preference understanding is insufficient
Solution Approach 1:
The system automatically merges individual preference data into aggregated group preferences through computational processing. The computer system combines data from multiple individual feedback sources to derive overall group preferences, maintaining simple data collection mechanisms while producing comprehensive group-level insights for informed decision-making.
Data Source
AI summary
The present disclosed is directed to systems, methods, and devices for obtaining feedback information from individuals to reveal group preferences and to systems, methods, and devices for enabling providers to provide outcomes which utilize, at least in part, the preferences of the group. For example, a system comprising a plurality of devices, wherein at least one device of the plurality of devices captures at least one feedback in one substantially simple transaction; and the at least one device of the plurality of devices sends the at least one captured feedback to at least one computer; and the at least one computer receives the least one feedback; and the at least one feedback can be given at one or more of the following: periodic time intervals, predefined time intervals, random time intervals, substantially random time intervals and substantially any time.