Building Load Control Using AI-Learned Actuation Sequences
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Solution Overview
Problem
Existing electrical systems require users to perform multiple switch combinations to activate loads, leading to complex user experiences and underutilization of control interfaces, with a need to reduce additional components and installation complexity.
Innovation Solution
A method and control device that utilize artificial intelligence to learn user habits through actuation sequences, allowing simplified control via a single button with intelligent and manual operating modes, and enable wireless communication for seamless integration with home automation systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple switches are concentrated in flush-mounted boxes to provide control points, then control coverage is improved, but user understanding of load-switch association becomes complex
Solution Approach 1:
The control device provides visual feedback through LEDs that illuminate to indicate which load will be activated by pressing a button. This feedback mechanism helps users understand the association between control points and loads, resolving the complexity issue while maintaining multiple control coverage
Solution Approach 2:
The control device can identify and control multiple different loads through a single interface, allowing one control point to serve multiple functions. This universal approach simplifies user interaction while maintaining the ability to control various loads
2Adaptability or versatility
If sequential relays are used to control lights successively, then control function is achieved, but user attempts to understand switch combinations increase
Solution Approach 1:
The control device performs preliminary identification of the user's intended load through sensor detection and analysis before actuation. By predicting which load the user wants to control based on movement detection and contextual information, the system prepares the correct association in advance, eliminating the need for multiple trial attempts
Solution Approach 2:
The system automatically identifies and configures the correct load-switch associations through sensors and algorithms without requiring user intervention or trial-and-error. The control device serves itself by detecting user presence and intent, then automatically establishing the correct control relationships
3Adaptability or versatility
If control interfaces are designed with multiple switches, then control capability is enhanced, but utilization of controls decreases
Solution Approach 1:
The control device dynamically adapts its behavior based on detected user habits and patterns. Through machine learning algorithms, the system evolves to predict user intentions and automatically configure control associations, making the interface more efficient over time while maintaining full control capability
Solution Approach 2:
The system changes operational parameters by learning user behavior patterns and adjusting control associations dynamically. By monitoring usage patterns and modifying the relationship between buttons and loads based on observed habits, the system optimizes control utilization while preserving full functionality
Data Source
Figure 1~2
AI summary
A method for controlling an electrical system, in particular for buildings, of the type comprising at least one control device and a plurality of loads, there being defined in the electrical system a plurality of actuation functions which can be carried out by means of the control device or by means of a plurality of control devices, the method comprising combining with the actuation functions the actuation of one or more of the loads, storing actuations carried out by a user, extracting from the actuations stored a sequence of actuations repeated by the user, modifying the combination of the actuation functions with the loads on the basis of the sequence of repeated actuations extracted.