PV Station Automation Object Detection Dataset and Pre-Trained Model by Revathy

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Explore Dataset

Here are a few use cases for this project:

Solar Energy Management: The "PV Station Automation" model could be utilized in the management of solar energy stations. Its ability to identify different classes of buttons, knobs, and slots could assist in automating the control and adjustment of solar panels for optimal energy collection based on weather and time of day.
Industrial Automation: This model would be advantageous in industrial settings such as production lines or advanced manufacturing plants. Automated systems could use it to identify operation buttons and slots, optimizing process time and efficiency and reducing potential for human error.
ATM Maintenance: Maintenance teams for ATMs or similar heavy machinery could use the model to help automate common tasks like removing or installing specific parts and components based on the button or knob classes recognized by the model.
Quality Control Inspection: The model could be used to automatically inspect products and devices for potential defects or errors in assembly. It could check the placement and configuration of buttons, knobs, and slots, alerting human operators if discrepancies are found.
Virtual Reality Training: This model could be the base for a virtual reality training tool used to train employees on finding and interacting with specific buttons, knobs, and slots on equipment or machinery, thereby improving training efficiency and effectiveness while reducing the risk of damage to actual equipment.

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{
                            pv-station-automation_dataset,
                            title = { PV Station Automation Dataset },
                            type = { Open Source Dataset },
                            author = { Revathy },
                            howpublished = { \url{ https://universe.roboflow.com/revathy/pv-station-automation } },
                            url = { https://universe.roboflow.com/revathy/pv-station-automation },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-04-20 },
                            }