Luminaire Classification via Sensor Data for Lighting Control
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Solution Overview
Problem
Traditional lighting control systems rely on preprogrammed logic that cannot optimally adapt to the specific characteristics of a space, leading to suboptimal lighting performance and energy consumption, and manual mapping of luminaires in complex environments is tedious and prone to errors.
Innovation Solution
A method and apparatus for classifying luminaires based on sensor data, including environmental characteristics like CO2, VOC, humidity, and air pressure, to assign them to predefined classes and adjust lighting control parameters, facilitating automatic or semi-automatic grouping and fine-tuning of lighting systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If preprogrammed lighting control logic is used, then general applicability is ensured, but optimized lighting performance for specific spaces cannot be achieved
Solution Approach 1:
The system continuously collects sensor data (occupancy, light levels, environmental conditions) and uses this feedback to dynamically adjust lighting control parameters. The control entity analyzes sensor signals in real-time and modifies lighting output accordingly, enabling the system to adapt to specific space characteristics while maintaining general applicability through automated learning and optimization.
2Measurement precision
If manual mapping of luminaires is performed, then accurate luminaire-position mapping is achieved, but the process is tedious and error-prone
Solution Approach 1:
The system automatically performs luminaire mapping by having each luminaire transmit its identifier and position information to the control entity. The control entity collects this data from multiple luminaires, processes the information to create a spatial map, and stores it in a database without requiring manual intervention. This self-service approach achieves accurate mapping while eliminating the tedious manual process.
3Ease of manufacture
If preprogrammed control parameters are used, then ease of installation is improved, but energy consumption optimization is compromised
Solution Approach 1:
The system transitions from static preprogrammed parameters to dynamic, real-time adjusted parameters. The control entity continuously monitors sensor data (occupancy status, light levels, environmental conditions) and dynamically modifies lighting parameters such as intensity, color temperature, and timing. This dynamic adjustment optimizes energy consumption by adapting lighting output to actual space conditions while maintaining ease of installation through automated parameter tuning.
Data Source
Figure 1A~1B
Figure 2~5
Figure 3
AI summary
According to an example embodiment, a method for classifying a plurality of luminaires based on respective sensor data captured at respective locations of the plurality of luminaires is provided. The method comprises: obtaining the respective sensor data for the plurality of luminaires, the respective sensor data for each luminaire comprising respective one or more time series of sensor values that each represent a respective environmental characteristic as a function of time for a respective one of the plurality of luminaires; and assigning at least one of the plurality of luminaires into one of two or more predefined luminaire classes based on variation of the sensor values in the respective one or more series of values in the sensor data obtained for the respective luminaire.