mobile detection Computer Vision Project

asu

Updated a year ago

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Classes (4)
drinking
eating
mobile use
smoking

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Description

Here are a few use cases for this project:

  1. Distracted Driver Detection: This model can be incorporated into vehicular systems to alert when drivers are distracted by activities such as mobile use, drinking, eating, or smoking, thereby improving road safety.

  2. Public Health Research: Researchers can use this model to anonymously collect data in public spaces to study the prevalence of unhealthy habits like smoking and high consumption of fast food, informing public health initiatives.

  3. Employee Productivity Monitoring: Companies could use this model to monitor employee focus and productivity, identifying when workers are distracted by mobile phones, eating, or smoking during work hours.

  4. Parental Control Applications: The model can be used to monitor children's activity, alerting parents if the child uses a mobile phone excessively or is detected smoking.

  5. Consumer Behaviour Analysis: Retail businesses can use the model to understand the habits of their customers better, such as the prevalence of mobile use in-store, food and drink consumption patterns, and smoking habits.

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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{
                            mobile-detection-l2iov_dataset,
                            title = { mobile detection Dataset },
                            type = { Open Source Dataset },
                            author = { asu },
                            howpublished = { \url{ https://universe.roboflow.com/asu-b6mtv/mobile-detection-l2iov } },
                            url = { https://universe.roboflow.com/asu-b6mtv/mobile-detection-l2iov },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-11-21 },
                            }
                        
                    

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