Luminaire Grid Functional Classification via Sensor Correlation
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Solution Overview
Problem
Existing systems for illuminating large environments, such as buildings, face challenges in efficiently distributing and powering sensors to control luminaire grids, as well as in manually classifying and grouping luminaires for different usage scenarios.
Innovation Solution
A method and system that utilize a grid of luminaires equipped with at least two sensors (light, acoustic, and motion sensors) to collect environmental data, which is then wirelessly forwarded to a central database for correlation and classification. This classification generates functional usage information for each luminaire, allowing adaptive behavior based on environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple environmental sensors are distributed in parallel to the luminaire grid, then environmental information collection is improved, but system complexity and cost increase
Solution Approach 1:
The patent combines multiple sensors (light sensor, acoustic sensor, motion sensor) into a single integrated sensor unit that is built into each luminaire. This merging approach eliminates the need for separate sensor distribution infrastructure while maintaining comprehensive environmental monitoring capabilities. The sensor unit is integrated directly into the luminaire housing, reducing system complexity.
Solution Approach 2:
Each luminaire is designed with multi-functionality, serving both as an illumination device and as an environmental sensing node. The integrated sensor unit enables the luminaire to perform multiple functions: providing light, detecting environmental conditions, and communicating status information. This universal design eliminates the need for dedicated sensor infrastructure.
2Adaptability or versatility
If manual classification of luminaires is performed, then functional grouping is achieved, but time consumption increases
Solution Approach 1:
The system performs self-classification by automatically analyzing sensor data from multiple luminaires to determine their functional groups. The classification is performed autonomously based on patterns detected in the sensor information, eliminating the need for manual intervention. The system serves itself by organizing luminaires into functional groups without human input.
Solution Approach 2:
The system continuously monitors sensor data from luminaires and uses this feedback to automatically classify and reclassify luminaires based on their operational patterns. The classification is dynamic and adapts to changing usage patterns, providing continuous feedback-driven organization of the luminaire grid into functional groups.
3Manufacturing precision
If luminaires are manually configured according to installation conditions, then individual luminaire setup is precise, but configuration complexity increases
Solution Approach 1:
Each luminaire performs self-configuration by automatically detecting its installation environment through integrated sensors and determining its own operational parameters. The luminaire autonomously adjusts its behavior based on detected conditions such as ambient light levels, presence of occupants, and acoustic environment, eliminating the need for manual configuration while maintaining precision.
Solution Approach 2:
The system automatically changes operational parameters of luminaires based on real-time sensor data. When environmental conditions change, the luminaire dynamically adjusts parameters such as illumination intensity, color temperature, and operational mode without manual intervention. This automated parameter adjustment maintains configuration precision while reducing complexity.
Data Source
AI summary
A method (20) for functional classification of luminaires (101a-d) arranged as a grid (100) has luminaires (101a-d) with at least two different sensors (103, 105, 107), such as at least two of a light sensor (103), an acoustic sensor (105) and a motion sensor (107). Output signals of the sensors (103, 105, 107) are supplied to a controller (109), and are wirelessly forwarded (23) along with timestamps and luminaire IDs to a gateway and then transmitted to a central database (403). The timestamps are used to correlate the sensor information signals (130) over a defined period of time, and to generate (27) functional classification information based on the correlations found. The functional classification information indicates a likelihood function of a certain usage of each luminaire, out of a given set of usage functions.