Lighting Fixture Location Mapping Using Environmental Profiles
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Solution Overview
Problem
Current lighting system commissioning methods are time-consuming, costly, and prone to errors, especially in symmetrical layouts, as they require manual intervention to resolve ambiguities and are not accurate due to signal interference and environmental factors.
Innovation Solution
A method and system that use sensors to generate environmental profiles for lighting fixtures and spatial locations, employing heuristic analysis to identify a single correct mapping of lighting fixtures to spatial locations with minimal or no manual intervention, reducing complexity and increasing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual commissioning methods are used to map lighting fixtures to spatial locations, then the process can be performed with simple equipment, but the process is time-consuming and costly
Solution Approach 1:
The lighting fixtures perform self-identification and self-location by emitting signals that are detected by sensors throughout the space. The system automatically maps fixtures to spatial locations without requiring manual intervention from commissioning engineers, enabling the system to commission itself
Solution Approach 2:
The manual mechanical process of physically locating and recording each fixture is replaced with an automated optical/electromagnetic signal-based system. Sensors detect signals from fixtures and use triangulation to automatically determine positions, eliminating the need for manual measurement and data entry
2Reliability
If manual inspection and data recording is performed for each lighting fixture, then accuracy can be maintained through careful verification, but the process is prone to human errors such as data input mistakes
Solution Approach 1:
The system eliminates human error by having fixtures self-identify through unique signals and automatically record their own locations through sensor detection and triangulation calculations, removing the manual data entry step that is prone to mistakes
Solution Approach 2:
The system uses sensor feedback to continuously detect fixture signals and automatically adjust the mapping. The triangulation process provides immediate verification of fixture positions, allowing the system to correct any positioning errors automatically without human intervention
3Productivity
If a skilled lighting commissioning engineer performs manual commissioning, then the process can be completed with appropriate expertise, but the cost increases significantly
Solution Approach 1:
The commissioning process is automated so that lighting fixtures themselves provide the data needed for mapping, eliminating the need for skilled commissioning engineers to manually locate and record each fixture. The system handles the complex commissioning tasks autonomously
Solution Approach 2:
The expertise and manual skills required for traditional commissioning are replaced with automated signal processing and triangulation algorithms. The computational system performs the complex calculations and spatial mapping that previously required human expertise
4Extent of automation
If test signals are used to cycle power levels of lights to identify locations, then the mapping process can be automated, but signal interference and environmental factors reduce accuracy
Solution Approach 1:
The system uses multiple sensors positioned at different locations to detect fixture signals. Each sensor provides localized measurements that are then processed together through triangulation, allowing the system to compensate for signal interference at any single location by using data from multiple perspectives
Solution Approach 2:
The system breaks symmetry in signal detection by using non-uniform sensor placement and differential signal processing. This asymmetric approach creates unique signal patterns for each fixture location, enabling the system to distinguish between fixtures even in symmetrical spaces and resolve ambiguities that would plague perfectly symmetrical detection systems
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system automates the commissioning process, reducing the need for manual intervention and improving accuracy, making it more efficient and cost-effective for large and complex lighting installations.
Implementation Method 1
a first dataset corresponding to a first environmental profile for the plurality of lighting fixtures based on measurements by the sensor of each of the plurality of lighting fixtures
Data Source
AI summary
Lighting systems and methods for lighting fixture location mapping, for example, using a combination of photosensing readings and/or other sensors to identify a correct mapping. These systems and methods may be used to resolve ambiguities that could not be resolved using other processes, such an auto-commissioning method that identifies more than one possible mapping of the lighting fixtures to spatial locations. Such ambiguities are typically found in floor plans that are symmetrical. The systems and methods of the present invention record and utilize environmental profiles, such as ambient lighting levels and occupancy patterns, to match lighting fixtures to their respective spatial locations and provide resolution to ambiguities in an auto-commissioning method that identifies more than one possible mapping of the lighting fixtures to spatial locations.