Smart Energy Profiles for Presence-Based Device Setting Control
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Solution Overview
Problem
Household and environmental energy-consuming devices often require frequent adjustments to meet varying user preferences, leading to inefficient energy consumption as settings are changed based on user presence, resulting in significant energy wastage.
Innovation Solution
A system 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, to optimize energy usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If device settings are frequently adjusted to meet varying user preferences, then user satisfaction is improved, but energy consumption increases
Solution Approach 1:
The system pre-calculates and stores optimal device settings for different user profiles before users actually need them. When users enter the environment, their pre-configured preferences are immediately applied without requiring real-time adjustments or calculations, thus satisfying user preferences while avoiding the energy waste of frequent setting changes.
Solution Approach 2:
The system dynamically adapts device settings based on real-time detection of user presence and identity. Instead of static settings or frequent manual adjustments, the system automatically transitions between different user profiles as users enter or leave the environment, optimizing both user satisfaction and energy efficiency by maintaining settings only when needed.
2Adaptability or versatility
If device settings are adjusted based on individual user preferences, then personalized comfort is improved, but system complexity increases
Solution Approach 1:
The system divides the environment into multiple zones with different devices and user profiles. Each zone can be independently configured with its own set of user preferences and device settings. This segmentation allows personalized comfort in each zone without requiring the entire system to become complex, as each segment operates semi-independently with its own simplified control logic.
Solution Approach 2:
The system uses a universal user profile structure that can be applied across multiple devices and zones. Instead of creating separate complex control systems for each device, a single profile framework handles temperature, lighting, entertainment, and other settings universally. This multi-functionality reduces overall system complexity while maintaining personalized comfort across diverse devices.
3Speed
If real-time detection and adjustment of device settings is implemented, then responsiveness to user needs is improved, but computational requirements increase
Solution Approach 1:
The system performs computationally intensive tasks in advance by pre-configuring user profiles and storing optimal device settings during low-demand periods. When users enter the environment, the system only needs to retrieve and apply pre-calculated settings rather than performing complex real-time computations, thus maintaining high responsiveness while minimizing computational power requirements during active operation.
Solution Approach 2:
The system detects and processes user presence information locally at the environment level rather than requiring centralized real-time computation for all devices. Each zone can independently detect user presence and apply appropriate settings using locally stored profile data, reducing the computational burden on any single system component while maintaining fast, responsive operation throughout the entire environment.
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.