Dynamically adaptive personalized smart energy profiles
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Solution Overview
Problem
Household energy-consuming devices often require frequent adjustments to meet varying user preferences, leading to inefficient energy consumption as members with different settings preferences enter or leave a room.
Innovation Solution
A facility dynamically configures energy-consuming and producing devices based on user profiles and presence information, calculating combined settings using weighted averages or geometric means to adjust parameters like temperature and brightness, considering user weights and presence duration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If device settings are adjusted frequently to meet varying user preferences, then user comfort is improved, but energy consumption increases
Solution Approach 1:
The system performs preliminary actions by detecting user presence in advance and proactively adjusting device settings before users actually need them. Presence detection triggers predetermined adjustment sequences, so when users enter a room, the environment is already optimized for their comfort, eliminating the need for reactive adjustments that waste energy.
Solution Approach 2:
The system implements feedback mechanisms where user preferences and presence information continuously inform device settings. The system monitors which adjustments users make manually and uses this feedback to refine automatic adjustment algorithms, creating a closed-loop system that learns optimal settings while minimizing unnecessary energy-consuming adjustments.
2Adaptability or versatility
If device settings are adjusted to accommodate multiple users with different preferences, then user satisfaction is improved, but system complexity increases
Solution Approach 1:
The system segments the environment into distinct zones with different device groups, each managed independently based on local user presence and preferences. Rather than controlling all devices globally, the system divides control authority across multiple segmented regions, simplifying the overall system architecture while maintaining adaptability to diverse user needs in different locations.
Solution Approach 2:
The system applies local quality by tailoring device settings specifically to each user's detected presence and stored preferences rather than applying uniform settings globally. Each user profile contains localized preference data that is applied only when that user is detected in a specific zone, allowing the system to accommodate multiple users with different preferences without requiring complex global coordination.
Data Source
AI summary
A facility employing systems, methods, and/or techniques for dynamically and adaptively configuring configurable energy consuming and producing devices (e.g., smart energy devices) based on user profiles and user presence information is disclosed. In some embodiments, the facility periodically detects the presence of users, and retrieves preference information for those users. For each of one or more configurable energy devices in the area, the facility generates a combined setting based on the preferences of each user present and adjusts the devices based on the combined settings. For example, if User A, User B, and User C are present in a room and User A's preferred temperature setting is 75° F., User B's preferred temperature setting is 68° F., and User C's preferred temperature setting is 70° F., the facility may generate a combined setting for a thermostat by taking the average value of the users in the room.