Detecting Recommissioning in Connected Lighting Systems
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Solution Overview
Problem
Connected lighting systems face challenges in automatically detecting recommissioning events, where changes in luminaire or sensor positions occur, leading to inaccurate data interpretation and analytics, as existing methods require manual intervention and do not account for changes in lighting signal features or IDs.
Innovation Solution
A method that automatically detects recommissioning by monitoring lighting signal features and IDs within a predetermined spatial demarcation, using clustering techniques to identify shifts in data clusters, and outputs an indication for updating the commissioning database, allowing for either manual or automatic correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual intervention is used to update commissioning database after luminaire or sensor position changes, then the commissioning database can be updated to reflect changes, but the process is error-prone and requires time-consuming manual collection and reporting of operational data
Solution Approach 1:
The system automatically detects recommissioning events by monitoring lighting signal features and performs database updates without human intervention. The analytics engine autonomously identifies when luminaires or sensors have been moved by analyzing changes in signal characteristics, and automatically triggers the necessary database updates, eliminating the need for manual data collection and reporting by commissioning personnel.
Solution Approach 2:
The system continuously monitors lighting signal features from luminaires and sensors, compares them against baseline commissioning data, and uses this feedback to automatically detect when position changes have occurred. This closed-loop feedback mechanism enables the system to identify recommissioning events in real-time and initiate corrective database updates automatically.
2Reliability
If manual commissioning updates are performed after system changes, then database accuracy can be maintained, but the process is time-consuming and reduces productivity
Solution Approach 1:
The system performs continuous monitoring of lighting signal features without interruption, constantly analyzing data to detect recommissioning events. This continuous operation eliminates the need for periodic manual checks and ensures that database updates are triggered immediately when changes occur, maintaining both high accuracy and rapid response times.
Solution Approach 2:
The manual mechanical process of collecting, transporting, and entering commissioning data is replaced by an automated electronic system that monitors signal features, processes data through the analytics engine, and updates the database automatically. This substitution of manual operations with automated computational processes dramatically increases productivity while maintaining data accuracy.
3Ease of operation
If the commissioning database is not updated after luminaire or sensor position changes, then manual updates are avoided, but data interpretation and analytics become inaccurate
Solution Approach 1:
The analytics engine serves as an intermediary between the raw lighting signal data and the commissioning database. It automatically processes the monitored signal features, identifies recommissioning events, and triggers database updates without requiring manual intervention. This intermediary system ensures that context information remains accurate while maintaining automatic operation.
4Device complexity
If existing commissioning methods are used without monitoring lighting signal features, then system complexity is reduced, but recommissioning detection capability is lost
Solution Approach 1:
The existing lighting control infrastructure is enhanced to perform multiple functions: it continues to provide lighting control while simultaneously monitoring lighting signal features for recommissioning detection. The analytics engine leverages the existing communication protocols and data streams, adding detection capability without requiring separate dedicated hardware systems, thus maintaining relative simplicity while enabling advanced functionality.
Data Source
AI summary
Method of detecting a change in a lighting system comprising a plurality of devices each comprising a luminaire and/or a sensor, wherein each respective one of the devices has a respective location recorded in a commissioning database in association with data reported by the respective device; the method comprising: identifying a subset of said devices located within a predetermined spatial demarcation; automatically monitoring a respective value of a characteristic of each of the devices in said subset, thereby forming a data cluster comprising the values of said characteristic for the subset; automatically detecting that one of one of the devices in the subset has been moved by detecting a shift in one of the cluster values relative to the rest of the values in the data cluster; and in response to said detection, automatically outputting an indication that the commissioning database is likely to require updating to reflect said change.