Empty Tanks Computer Vision Project
Updated a year ago
Metrics
Here are a few use cases for this project:
-
Fuel Stations Efficiency: This model can help automate the process monitoring fuel levels in vehicles at gas stations. Recognizing cars with empty tanks can aid in optimizing queues and improving overall service efficiency.
-
Traffic Management: Traffic control systems can use this model to predict potential breakdowns of vehicles running out of fuel, enabling preemptive measures to maintain a steady flow of traffic.
-
Vehicle Towing & Maintenance Services: This computer vision model could assist towing and vehicle maintenance services by identifying vehicles that have run out of fuel, allowing for precise location and quicker response time.
-
Auto Insurance Analysis: Insurance companies could leverage this model to determine risky behavior or negligence related to keeping vehicles properly fueled. This could affect premium calculations or claim assessments.
-
Roadside Assistance: Roadside assistance apps or services can integrate this model for real-time fuel status detection, providing a useful feature for drivers who may need fuel assistance.
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
empty-tanks_dataset,
title = { Empty Tanks Dataset },
type = { Open Source Dataset },
author = { pavloniym },
howpublished = { \url{ https://universe.roboflow.com/pavloniym-lddba/empty-tanks } },
url = { https://universe.roboflow.com/pavloniym-lddba/empty-tanks },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { oct },
note = { visited on 2024-12-22 },
}