Automated Meter Reading via Image Recognition and Machine Learning
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Solution Overview
Problem
Manual reading of meters in processing facilities is prone to errors due to factors like poor lighting, parallax, and human judgment/recording errors.
Innovation Solution
The implementation of a system that uses image recognition and machine learning techniques to automatically capture and process images of meters, detect target regions, and extract measurement information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual reading of meters is performed by operators, then human judgment and recording can be applied, but errors occur due to poor lighting, parallax, and human judgment/recording errors
Solution Approach 1:
The patent replaces the manual mechanical reading process with an automated image-based system. A camera captures images of meter dials, and image processing algorithms automatically extract measurement values, eliminating human operators from the direct reading process. This substitution resolves the contradiction by providing consistent, error-free automated reading that is not affected by lighting conditions, parallax, or human judgment errors.
Solution Approach 2:
The patent introduces an intermediary image processing system between the meter and the data recording system. The system captures images of the meter dial and uses automated algorithms to interpret the measurement, serving as a mediator that eliminates direct human involvement in the reading process while maintaining measurement accuracy and consistency.
2Measurement precision
If automated image-based reading is implemented, then human error is reduced and accuracy improves, but system complexity increases due to image processing requirements
Solution Approach 1:
The patent creates a visual copy (image) of the meter dial and processes this copy to extract measurement information. By working with an image copy rather than requiring direct physical access to the meter, the system simplifies the overall architecture while maintaining high measurement precision. The image serves as a faithful reproduction that can be analyzed automatically without complex mechanical interfaces.
Data Source
AI summary
Methods, systems, and devices for equipment reading in a factory or plant environment are described, including: capturing an image of an environment including a measurement device; detecting a target region included in the image, the target region including at least a portion of the measurement device; determining identification information associated with the measurement device based on detecting the target region; and extracting measurement information associated with the measurement device based on detecting the target region. In some aspects, detecting the target region may include: providing the image to a machine learning network; and receiving an output from the machine learning network in response to the machine learning network processing the image based on a detection model, the output including the target region.