Gas_Meter_v3 Object Detection Dataset and Pre-Trained Model by GasMeterDialsFBDetectorn

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Explore Dataset

Here are a few use cases for this project:

Utility Monitoring: Use Gas_Meter_v3 to automatically read and record gas meter readings for residential and commercial properties, improving the efficiency and accuracy of utility monitoring and billing processes.
Leak Detection and Maintenance: Implement Gas_Meter_v3 in IoT devices to monitor meter dials for irregularities or fluctuations in gas consumption, allowing for early detection of potential leaks and proactive maintenance.
Energy Conservation Initiatives: Utilize Gas_Meter_v3 data to analyze trends in gas consumption and develop tailored energy conservation programs for residential and commercial areas, promoting sustainable practices.
Emergency Response: Integrate Gas_Meter_v3 into emergency response systems to track gas consumption in real-time during natural disasters or accidents, allowing authorities to manage distribution and locate potential hazards quickly.
Remote Meter Reading: Use Gas_Meter_v3 to enable remote meter reading services and reduce the need for manual, in-person meter reading, minimizing human errors and reducing operational costs for utility providers.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            gas_meter_v3_dataset,
                            title = { Gas_Meter_v3 Dataset },
                            type = { Open Source Dataset },
                            author = { GasMeterDialsFBDetectorn },
                            howpublished = { \url{ https://universe.roboflow.com/gasmeterdialsfbdetectorn/gas_meter_v3 } },
                            url = { https://universe.roboflow.com/gasmeterdialsfbdetectorn/gas_meter_v3 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-04-25 },
                            }