š Computer vision can be used to read analog meters in real time.
š” Switching to digital meters may not always be feasible or cost-effective.
š Analog meters can be connected to a server, allowing remote access to readings.
š By using computer vision, it is possible to read analog meters for water, gas, and electricity.
ā ļø Real-time warnings can be generated if there is a significant deviation from previous readings.
š A control panel can be created, allowing users to monitor multiple meters and compare readings over time.
š· Position a webcam near the analog meter to capture real-time footage.
š„ļø Use a Raspberry Pi or a server as the device to process the footage.
š¢ OpenCV software is utilized to read and extract numbers from the meter.
š” By using OpenCV software, analog meters can be read and converted into real numbers.
ā° The readings from the meters can be obtained in real-time, allowing for immediate updates.
š The OpenCV software can be connected to a website, such as waterreading.com, to access the readings online.
š Using computer vision, you can read analog meters (water, gas, electricity) in real-time from anywhere in the world.
š§ You can set up a script to send notifications via email, SMS, or WhatsApp message when a certain reading threshold is reached.
š” The structure and settings of the numbers on the meter may vary, but OpenCV can handle different configurations.
š Using OpenCV and computer vision, we can read the position of the pointer on analog meters.
š¢ By creating a small deep learning model, we can read the numbers on the meter as well.
š The model may require calibration or retraining to ensure accurate readings.
š Using OpenCV with Python, you can easily read analog meters by detecting the red line that indicates the value.
š” Implementing this solution can help industries save costs and improve their production by digitizing their processes.
š» If you are a developer, researcher, or someone learning computer vision, there is a free one-hour workshop available on the basics of computer vision and object detection and tracking.