Occupancy interaction detection
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Solution Overview
Problem
Building control systems face challenges in effectively tracking motion and detecting occupancy interactions within retail environments to enhance customer engagement and energy management.
Innovation Solution
A system comprising multiple sensors and a controller that sense and track motion, identify interactions between occupants by detecting proximity and duration within a threshold distance, and generate profiles for sales associates and customers to measure engagement effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are deployed to track motion and detect occupancy interactions, then measurement precision and occupancy detection capability are improved, but device complexity and cost increase
Solution Approach 1:
The system divides the monitoring area into multiple zones with sensors strategically positioned to detect motion and occupancy interactions. Each sensor monitors specific segments of the space, and the controller integrates data from these segments to achieve comprehensive occupancy detection without requiring complete sensor coverage of every area.
Solution Approach 2:
The controller performs multiple functions including receiving sensor data, tracking occupant locations, detecting interactions based on proximity thresholds, generating engagement metrics, and controlling building systems. This multi-functionality consolidates what could be separate systems into a single integrated platform, improving measurement precision while managing device complexity.
2Loss of information
If sensor data is continuously processed to track occupant locations and detect interactions, then occupancy engagement measurement capability is improved, but energy consumption increases
Solution Approach 1:
The system processes sensor data at defined intervals rather than continuously, tracking occupant locations and detecting interactions based on periodic sensor readings. The controller evaluates occupancy interactions by comparing location data across time intervals, which reduces computational load and energy consumption while maintaining adequate tracking accuracy for engagement measurement.
Solution Approach 2:
The system automatically processes sensor data and generates engagement metrics without requiring continuous external intervention. The controller autonomously evaluates occupancy interactions, tracks customer engagements, and produces reports, reducing the need for constant system activation and lowering overall energy consumption while maintaining information accuracy.
3Measurement precision
If interaction detection uses strict proximity thresholds to identify customer-associate engagements, then measurement precision is improved, but false detection rate increases
Solution Approach 1:
The system uses dynamic proximity thresholds and time-based evaluation rather than fixed distance criteria. Interaction detection considers both spatial proximity and temporal duration, allowing the system to adapt to different interaction scenarios. This dynamic approach maintains measurement precision by detecting genuine interactions while reducing false positives caused by brief accidental proximity events.
Solution Approach 2:
The controller continuously monitors sensor data and adjusts interaction detection based on patterns observed over time. By evaluating multiple data points and comparing against established criteria, the system provides feedback mechanisms that distinguish genuine customer-associate interactions from false proximity events, improving accuracy while minimizing false detections.
Data Source
AI summary
Apparatuses, methods, apparatuses and systems for occupancy interaction detection, are disclosed. One occupancy interaction detection system includes a plurality of sensors located within an area, the plurality of sensors operative to sense at least motion of a first occupant and a second occupant of the area, and communication links between each of the sensors and a controller. For an embodiment, the controller operative to receive sense data from the plurality of sensors, track locations of the first occupant of the area based on the sensed motion of the first occupant, track locations of the second occupant of the area based on the sensed motion of the second occupant, and identify an interaction between the first occupant and the second occupant, comprising detecting the first occupant to be within a threshold distance of the second occupant.