Smart Scene Management for Adaptive Home Automation Schedules
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Solution Overview
Problem
Conventional home automation systems face difficulties in dynamically adjusting automated features in response to changes in a homeowner's schedule, requiring manual reprogramming and limiting flexibility and convenience.
Innovation Solution
A home automation system that utilizes sensors, a control panel, and cloud monitoring to analyze user activity patterns, allowing for intelligent modification and creation of dynamic scenes through Big Data analysis, enabling automatic adjustment of environmental settings and energy utilization without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional home automation systems use fixed automated schedules, then system reliability is maintained, but adaptability deteriorates when homeowner schedules change
Solution Approach 1:
The system automatically detects user presence and activity patterns through sensors and cloud monitoring, then autonomously adjusts automated scenes without requiring manual reprogramming. The control panel independently learns schedule changes and modifies scene timings based on observed user behavior patterns.
Solution Approach 2:
The system continuously monitors user interactions and sensor data, feeds this information back to the control panel, which then automatically adjusts scene schedules. This closed-loop feedback mechanism enables the system to adapt to schedule changes by learning from actual user presence and activity patterns.
2Adaptability or versatility
If automated features are manually reprogrammed to accommodate schedule changes, then adaptability improves, but loss of time increases due to manual intervention
Solution Approach 1:
The system performs self-adjustment by automatically detecting schedule changes through sensor data and cloud monitoring, eliminating the need for manual reprogramming. The control panel independently modifies scene timings based on learned user patterns, saving user time and effort.
Solution Approach 2:
The system proactively detects and learns schedule changes before they become problematic, continuously monitoring user presence patterns and preemptively adjusting automated scenes to match new schedules, avoiding the need for reactive manual reprogramming.
3Adaptability or versatility
If the system continuously monitors user patterns for automatic adjustment, then adaptability improves, but use of energy increases due to continuous data collection and processing
Solution Approach 1:
The system performs pattern analysis and scene adjustments at periodic intervals rather than continuously. Sensors collect data periodically, the control panel processes patterns at scheduled intervals, and scenes are updated based on accumulated learning, reducing energy consumption while maintaining adaptability.
Solution Approach 2:
The system accumulates and pre-processes sensor data over time before performing comprehensive pattern analysis. By collecting data continuously but analyzing and acting on patterns periodically, the system prepares adjustment decisions in advance, reducing the computational energy required during active adjustment periods.
Data Source
AI summary
An automation system including sensors that detect threats within a secured area, a plurality of prospective events defined within a memory of the automation system, each event including at least a physical change in an environment of the secured area, a time of execution of the physical change and a corresponding actuator that causes the physical change, a processor of the automation system that periodically activates the corresponding actuator at the time of each of the plurality of events, a processor that monitors each of the plurality of sensors for activation by an authorized human user and that saves a record of each activation to a cloud memory and a cloud processor that monitors the saved activation records of each sensor over a time period, determines a difference between the saved activations and the plurality of events and that modifies the plurality of events based upon the determined differences.