Occupancy Simulation Control Using Activity Preference Matching
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Solution Overview
Problem
Current security systems for simulating occupancy of a building or dwelling are limited in providing a realistic and instant simulation, as they require a learning period to establish usage patterns or react only to noise events, failing to offer a consistently effective deterrent against theft and vandalism.
Innovation Solution
A method and system that uses a matcher algorithm to match user preferences with activity attributes and external data to generate a time sequence for simulated activities, allowing for instant customization and integration with lighting, audio, and appliance controls to create a realistic simulation of human presence, including visual and audio simulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a learning mode is used to record and store usage patterns over an extended time period, then the realism of occupancy simulation is improved, but the time required to deploy the system increases
Solution Approach 1:
The system performs preliminary actions by pre-defining multiple activity templates that represent typical human behaviors (e.g., waking up, having breakfast, going to work). These templates are prepared in advance with associated timing and duration parameters, allowing the system to immediately generate realistic occupancy simulations without requiring a learning period. The control unit randomly selects and executes these pre-prepared templates to create convincing occupancy patterns.
Solution Approach 2:
The system changes parameters by allowing dynamic adjustment of activity template parameters such as start time, duration, and frequency. The control unit can modify these parameters based on user input or environmental conditions, enabling the simulation to adapt to different scenarios while maintaining realism. This parameter flexibility allows the system to provide realistic simulation immediately without lengthy learning periods.
2Adaptability or versatility
If timing control systems are used to turn lights on and off, then occupancy simulation is provided, but the realism and effectiveness as a deterrent is reduced
Solution Approach 1:
The system transitions from static timing control to dynamic activity-based control. Instead of fixed schedules, the control unit dynamically selects and executes activity templates that represent realistic human behaviors. Each activity template contains dynamic parameters such as variable durations, random intervals between activities, and context-dependent timing. This dynamic approach creates more convincing occupancy patterns that adapt to different scenarios, significantly improving deterrent effectiveness.
Solution Approach 2:
The system implements periodic action through structured activity templates that represent recurring human behaviors (e.g., daily routines, meal times). The control unit executes these templates in a periodic manner with realistic intervals, creating patterns that mimic actual occupancy. This periodic structure based on human behavior patterns enhances the realism and deterrent value compared to simple random timing.
3Measurement precision
If noise processing modules are used to detect predefined noise signals, then response to human presence is improved, but the system only works reactively rather than proactively
Solution Approach 1:
The system inverts the conventional approach by switching from reactive noise-based activation to proactive activity-based simulation. Instead of waiting for noise signals to trigger occupancy simulation, the control unit proactively executes activity templates that create occupancy patterns before any detection event occurs. This inversion allows the system to provide continuous proactive deterrent simulation while maintaining the ability to respond to noise events when needed.
Data Source
AI summary
A method, device and system for simulating the presence of humans includes the method steps of defining activity attributes as input data and defining user preferences as input data. As an output, a time sequence for simulated activities is generated, while the method, device and system should provide an exceedingly realistic simulation of the presence of humans for any application where occupancy simulation is advantageous. This is reached in that user preferences are matched with attributes of activity respectively in that a control unit of a device or within a system is configured to match user preferences with attributes of activity for the generation of the sequence list for simulated activities.