Directional Gate Occupancy Tracking for AI Responsive Spaces
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Solution Overview
Problem
Existing systems lack the capability to effectively track occupancy and additional conditions of a physical area in real-time and respond automatically with intelligent actions, limiting their efficiency and adaptability.
Innovation Solution
A method and system that define logical boundaries for a physical area, monitor directional gates for ingress and egress, maintain occupancy counts, track additional conditions, and apply AI processing to trigger responsive actions, such as adjusting climate or security systems, using sensors and machine learning to improve action efficacy over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If real-time monitoring and AI processing are implemented, then system intelligence and automatic responsiveness are improved, but device complexity and computational requirements increase
Solution Approach 1:
The system segments the monitoring and processing functions into distinct modules: occupancy detection module, condition tracking module, and AI processing module. This segmentation allows each module to specialize in specific tasks, improving overall system intelligence while managing complexity through modular architecture.
Solution Approach 2:
The patent introduces an intermediary AI processing layer that sits between the raw sensor data collection and the final automated actions. This intermediary layer processes occupancy counts and additional conditions to generate intelligent decisions, enabling automatic responsiveness without requiring direct complex connections between all system components.
2Loss of information
If multiple conditions are tracked simultaneously, then measurement comprehensiveness is improved, but measurement precision and data processing complexity increase
Solution Approach 1:
The system employs a universal data collection framework that can simultaneously track multiple conditions (occupancy, temperature, humidity, light, etc.) through a single integrated architecture. This multi-functional approach allows comprehensive data collection without requiring separate specialized systems for each condition, maintaining measurement precision while achieving comprehensiveness.
Solution Approach 2:
The AI processing module continuously receives feedback from multiple condition sensors and adjusts its analysis accordingly. This feedback mechanism allows the system to prioritize and refine measurements based on current conditions, maintaining precision across multiple tracked parameters by dynamically allocating processing attention.
Data Source
AI summary
Logical boundaries enclosing a physical area are defined. A segment of the logical boundaries is defined as a directional gate, wherein traversing the gate into the physical area is defined as an ingress and traversing the gate out of the physical area is defined as an egress. The directional gate is monitored, and ingresses and egresses are detected. An occupancy count of the physical area is maintained, based on monitoring the gate and detecting ingresses and egresses. One or more conditions are tracked in addition to the occupancy count. Artificial intelligence (AI) processing is applied to the maintained occupancy count and the additional tracked condition(s), in real-time as the monitoring, maintaining and tracking are occurring. One or more responsive actions are automatically taken as a result of applying the AI processing to the maintained occupancy count and the additional tracked condition(s).