Automated Luminary Fixture Detection via Ceiling Scan Analysis
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Solution Overview
Problem
Current building energy audits for lighting are laborious, error-prone, and inaccurate, relying on manual counting of luminary fixtures, which hinders efficient estimation of energy savings and lighting upgrades.
Innovation Solution
The use of an electronic image capture device and computing device to capture a ceiling scan, generate a synthetic ceiling image, identify luminary candidates, and estimate power consumption by converting pixel areas into metric areas using a linear least square method, thereby automating the detection and quantification of luminary fixtures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual counting of luminary fixtures is used, then the process is simple to implement, but the accuracy and efficiency are poor
Solution Approach 1:
The patent replaces the manual mechanical counting process with an automated electronic image capture and processing system. The system uses electronic image capture devices to photograph ceiling areas and computational algorithms to automatically detect and count luminary fixtures, substituting human visual inspection and manual counting with electronic automation to achieve higher accuracy and efficiency
Solution Approach 2:
The patent creates a digital copy of the ceiling area through electronic image capture. By photographing the ceiling and processing the image data, the system generates a digital representation that can be analyzed computationally to identify luminary fixtures, replacing the need for direct physical inspection
2Productivity
If manual energy audit is performed, then the method is straightforward, but the labor consumption and time required are high
Solution Approach 1:
The patent replaces the labor-intensive manual energy audit process with an automated electronic system. Image capture devices and computational processing automatically perform the tasks of locating, counting, and characterizing luminary fixtures, dramatically reducing the time and labor required while maintaining or improving audit quality
Solution Approach 2:
The system enables the energy audit process to perform itself through automation. The electronic image capture and processing system independently completes the luminary detection and counting tasks without requiring continuous human intervention, allowing the audit process to serve itself and significantly improving productivity
3Reliability
If manual counting method is used, then the equipment required is minimal, but the error rate and labor requirements are high
Solution Approach 1:
The patent replaces manual counting with automated electronic image capture and processing. The system uses electronic devices to capture ceiling images and computational algorithms to automatically identify and count luminary fixtures, eliminating human error and providing reliable, consistent results through automation
Solution Approach 2:
The system incorporates feedback mechanisms where the processed image data is analyzed to identify luminary fixtures, and the results can be verified or adjusted. This feedback loop ensures high reliability by allowing the system to self-correct and validate its detections
Data Source
AI summary
Methods for detecting a number of luminary fixtures in an indoor environment using an electronic image capture device and electronic computing device are presented, the methods including: capturing a ceiling scan of the indoor environment with at least the electronic image capture device; analyzing a synthetic ceiling image corresponding with the ceiling scan using the electronic computing device to identify a number of luminary candidates; and converting the number of luminary candidates to define the number of luminary fixtures. In some embodiments, the capturing the ceiling scan further includes: moving the electronic image capture device through the indoor environment; capturing the indoor environment; generating a point cloud of the indoor environment; colorizing the point cloud; extracting the colored point cloud of a ceiling; dividing the extracted point cloud into a number of rooms; and generating the synthetic ceiling image for each of the number of rooms.