Powerline Computer Vision Project

Power

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Classes (9)
Bird Nest
Bolt Missing
Corrosion
Cracks in structure
Insulator Damage
Nut Bolt Missing
Overloading and sagging
R Pin Missing
Tree and vegetation

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Description

Here are a few use cases for this project:

  1. "Utility Infrastructure Maintenance": This use case is focused on assisting utility companies to monitor and maintain their infrastructure. By identifying various anomaly classes such as cracks in the structure, missing components, and corrosion, the model can be used to alert maintenance crews about potential risks, therefore enabling proactive rectification.

  2. "Ecosystem Impact Analysis": The model can be utilized by environmental scientists to study the impact of power line towers on local ecosystems, such as identifying instances of bird nests on power line towers or the effect of vegetation growth on these man-made structures.

  3. "Monitoring Overloading and Sagging": Power companies could deploy the model in regular inspections to determine lines that are overloaded or sagging due to excessive load, thereby preventing breaks that could result in power outages.

  4. "Disaster Risk Management": This model can be employed by emergency authorities for monitoring power lines during extreme weather events. Early identification of insulator damage, missing parts or overloading can facilitate prompt repair before these escalate into larger issues such as explosions or outages.

  5. "Automated Compliance Check": Government or regulatory agencies might use this model for assessing utility companies' observation of maintenance guidelines, by analyzing the frequency of anomalies such as bolt, nut or R pin missing and compliance with vegetation clearance norms.

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Cite This Project

LICENSE
CC BY 4.0

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

                        @misc{
                            powerline-h52e9_dataset,
                            title = { Powerline Dataset },
                            type = { Open Source Dataset },
                            author = { Power },
                            howpublished = { \url{ https://universe.roboflow.com/power-8hp4p/powerline-h52e9 } },
                            url = { https://universe.roboflow.com/power-8hp4p/powerline-h52e9 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-11-21 },
                            }
                        
                    

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