Smart Home Occupant Movement Pattern Prediction
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Solution Overview
Problem
Pattern recognition technologies have not been widely utilized in smart home management to determine destination and duration of stay, limiting the ability to automate and optimize home settings based on occupant behavior.
Innovation Solution
A method and system that uses pattern matching to predict a destination location and duration of stay within a smart home by detecting individual movements, comparing them to a data store of patterns, and activating or deactivating fixtures accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If pattern recognition is not utilized in smart home management, then the system remains simple and easy to implement, but the ability to automate and optimize home settings based on occupant behavior is limited
Solution Approach 1:
The system automatically detects occupant presence, identifies destinations, and controls fixtures without manual intervention. The pattern recognition system serves itself by continuously learning from observed movement patterns and automatically applying this knowledge to optimize home settings, eliminating the need for programming or configuration by users.
Solution Approach 2:
The patent replaces manual control mechanisms with automated pattern recognition and machine learning systems. Instead of users manually programming smart home behaviors, the system uses computational algorithms to automatically learn and predict occupant patterns, substituting mechanical/manual control with intelligent automated control.
2Measurement precision
If pattern recognition algorithms are implemented to track individual movements, then predictive capabilities are enhanced, but the computational resources and processing time required increase
Solution Approach 1:
The system focuses computational resources on tracking and analyzing only the movements and behaviors of occupants within the smart home environment, rather than processing all possible data. By concentrating on relevant partial information (occupant movements, destination predictions, fixture control), the system achieves high prediction accuracy without requiring excessive computational energy.
Solution Approach 2:
The system pre-processes and stores movement patterns as they occur, building a database of occupant behaviors over time. This preliminary action allows the system to quickly retrieve and match patterns during prediction without performing heavy real-time computation, reducing energy consumption during actual prediction operations.
3Adaptability or versatility
If the system tracks and analyzes individual movement patterns continuously, then the personalization and adaptability improve, but the privacy concerns and data security risks increase
Solution Approach 1:
The system extracts only the essential movement pattern information needed for prediction (origination location, destination, duration) while leaving out personally identifiable information. By taking out only the necessary data elements for pattern recognition and discarding or not storing sensitive personal details, the system achieves personalization capability while minimizing privacy risks.
Data Source
AI summary
A method for destination and duration of stay determination in a geographically bounded area such as a smart home includes detecting movement by an identified individual in an origination location of a geographically bounded area and retrieving a contemporaneously generated pattern of movement for the individual. The method additionally includes comparing the pattern for the identified individual to a set of patterns in a pattern data store and predicting from a matching pattern both a destination location in the geographically bounded area and a duration of time at which the identified individual is to remain at the destination location. Finally, the method includes directing activation of a fixture at the destination location responsive to predicting the destination location, and directing deactivation of a fixture at the origination location responsive to predicting a duration of time that exceeds a threshold value.