Cross road traffic monitoring label Object Detection Dataset and Pre-Trained Model by VV Ca

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Explore Dataset

Here are a few use cases for this project:

Traffic Management: Given its capability to identify different types of vehicles, this model could be used by city planners and traffic management authorities to monitor vehicular activities at various intersections. This data could aid in optimizing traffic signals timings for smoother flow and reducing congestion.
Safety Enhancement: The model could be used to enhance safety in accident-prone areas by closely monitoring the type and numbers of vehicles crossing any particular junction. This could act as a preventive measure against potential accidents, especially involving heavier vehicles and smaller ones like bicycles and motorbikes.
Urban Planning: By analyzing the types of vehicles predominantly used in a particular city or region, the model could provide valuable insights for urban planning. For instance, regions with a high number of bicycles may benefit from more bicycle lanes.
Fleet Management: Companies with large fleets of cars, trucks, buses or bikes could use this model to monitor and assess their vehicles' movement in real time. It can help optimize routes and schedules, thus improving logistical efficiency.
Law Enforcement: Law enforcement agencies could utilize the model to detect abnormalities and potentially illegal activities like street racing, unregistered heavy vehicles, or abnormal vehicle numbers at certain times. This could aid in proactive law enforcement and community safety measures.

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{
                            cross-road-traffic-monitoring-label_dataset,
                            title = { Cross road traffic monitoring label Dataset },
                            type = { Open Source Dataset },
                            author = { VV Ca },
                            howpublished = { \url{ https://universe.roboflow.com/vv-ca-byaak/cross-road-traffic-monitoring-label } },
                            url = { https://universe.roboflow.com/vv-ca-byaak/cross-road-traffic-monitoring-label },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-04-26 },
                            }