Control Hub Rule Layers for Interfering Event Handling
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Solution Overview
Problem
Existing home automation and assistance systems lack the ability to adapt to real-time interfering events and user-specific scenarios, leading to inefficient device usage and increased computational and storage demands.
Innovation Solution
A method and control hub that acquire historical data to establish a base routine rule layer, detect interfering events through sensor and device data, generate an additional rule layer to accommodate these events, and store it for future use, allowing personalized and efficient device control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system processes all sensor data and device data in real-time to handle interfering events, then the system can adapt to new scenarios, but computational and storage demands increase
Solution Approach 1:
The rule system is segmented into a base routine rule layer and an additional routine rule layer. The base layer contains general rules derived from historical data, while the additional layer contains specific rules for interfering events. This segmentation allows the system to process only relevant rules rather than all possible scenarios, reducing computational and storage demands while maintaining adaptability.
Solution Approach 2:
The system performs preliminary action by deriving the base routine rule layer in advance from historical sensor data and device data. This pre-processed base layer serves as a foundation that reduces the need for real-time processing of all historical data when new interfering events occur, thereby reducing computational and storage demands during operation.
2Adaptability or versatility
If the system stores comprehensive historical data for rule generation, then personalized control is achieved, but storage requirements increase
Solution Approach 1:
The system extracts only the essential patterns and rules from comprehensive historical data to create the base routine rule layer. Instead of storing and processing all raw historical sensor data and device data, the system extracts meaningful behavioral patterns and stores them as rules, achieving personalized control while significantly reducing storage requirements.
3Device complexity
If the system uses a single unified rule layer for all scenarios, then system complexity is reduced, but the system cannot adapt to interfering events
Solution Approach 1:
The rule system is made dynamic by introducing the additional routine rule layer that can be generated and applied when interfering events are detected. The system transitions from a static base layer to a dynamic multi-layer structure that adapts to new scenarios. This dynamic approach maintains relative simplicity while enabling adaptability, as the additional layer is only created when needed rather than pre-defining all possible scenarios.
Data Source
AI summary
According to an aspect, there is provided a computer-implemented method for modifying a rule at a control hub, wherein the control hub is connected to one or more devices and is configured to deliver at least one of audio and/or visual information. The method comprises: acquiring (210) a base routine rule layer for controlling the devices in a usage scenario, wherein the base routine rule layer is based on historical data associated with a routine of a user; acquiring (220) sensor data and/or device data from at least one of the one or more devices; determining (230) whether there is an interfering event based on evaluation of the sensor data and/or device data, wherein the interfering event conflicts with the base routine rule layer; generating (240), upon determining that there is an interfering event, an additional routine rule layer based on the sensor data and/or device data; executing the additional routine rule layer; and storing the additional routine rule layer in a rule database at the control hub.