AI Presence Simulation for Realistic Occupancy Lighting
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Solution Overview
Problem
Existing presence mimicking technologies based on schedules are predictable and can be easily distinguished from actual occupancy, leading to increased user burden and error in defining complex schedules, which may result in unrealistic behavior patterns.
Innovation Solution
The system employs artificial intelligence (AI) behavior simulation to model virtual occupant profiles, allowing users to define intrinsic human characteristics rather than lighting schedules, generating realistic sequences of control actions for lighting systems to simulate occupant presence, thereby making the environment appear occupied.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If schedule-based presence mimicking is used, then the system can simulate occupancy automatically, but the simulation becomes predictable and easily distinguishable from actual occupancy
Solution Approach 1:
The patent transforms static schedule-based control into dynamic behavior simulation. Instead of fixed timing patterns, the system uses virtual occupants with personality traits, routines, and decision-making algorithms that adaptively determine lighting actions. This creates unpredictable, realistic occupancy patterns that vary based on simulated occupant states and contexts.
Solution Approach 2:
The patent creates virtual copies of real occupants (virtual occupants) that replicate human behavior patterns. These virtual entities have profiles containing demographic information, routines, preferences, and personality characteristics that drive realistic lighting interactions, making the simulation indistinguishable from actual occupancy.
2Reliability
If complex scheduling options are provided to users, then the realism of presence simulation can be improved, but the user burden and complexity of configuration increase significantly
Solution Approach 1:
The system performs self-configuration through automated profile generation. The controller automatically creates virtual occupant profiles by analyzing historical lighting data and occupancy patterns, eliminating the need for users to manually configure complex schedules. The system serves itself by learning and generating realistic behavior patterns autonomously.
Solution Approach 2:
The patent replaces manual scheduling configuration with AI-driven behavior simulation. Instead of users mechanically setting complex time-based schedules, an intelligent algorithm automatically generates and adjusts lighting patterns based on virtual occupant profiles, substituting user effort with automated intelligence.
3Reliability
If randomized schedules are used, then some predictability can be reduced, but detectable patterns still emerge over time
Solution Approach 1:
The system employs dynamic behavior models where virtual occupants make context-dependent decisions about lighting usage. Rather than random or fixed patterns, the simulation adapts based on simulated occupant states, routines, and environmental factors, creating naturally variable patterns that mirror real human behavior without requiring complex randomization algorithms.
Data Source
AI summary
A presence simulation system comprises a user interface (32), a profile generator (34) and a presence simulator (35). The profile generator (34) is configured to generate in electronic storage a plurality of virtual occupant profiles (22) according to profile creation inputs received via the user interface (32), each virtual occupant profile comprising user-defined virtual occupant identity data. The presence simulator (35) is configured to generate a sequence of simulated control actions, by applying a behaviour simulation algorithm to the user-defined virtual occupant identity data of the electronically-stored virtual occupant profile. A lighting controller (40) configured to vary at least one characteristic of light emitted by at least one luminaire according to the sequence of simulated control actions.