FOULSTOP

Inspiration

We were inspired by the study that showed the astounding amount of time young people spent on a screen, which could be up to four hours, and the negative effects on their behaviour and personality from extensive exposure to violent videos and other media. It was surprising to see just how prevalent small slips of profanity or graphic scenes of violence are on sites such as YouTube. These are the types of sites where kids actually spend a lot of time watching.

What it does

Our solution is a chrome extension that when enabled with a simple toggle, will recognize each video the user navigates to on YouTube via the unique ID within the link and will either pull up an existing .txt file with time stamps of places to mute or skip ahead of. If the video has not been curated by the community , it will create a new .txt file in which the community will click a simple button ‘FoulStop!’ This will add a commented field within the .txt file with the time stamp of when the user clicked for us to review.

How we built it

We developed a chrome extension through JavaScript with a main manifest JSON to connect everything into a functional extension - this involved HTML, CSS and JavaScript. We also tried to connect all this through MangoDB Atlas for it to work seamlessly via the cloud however we ran into issues trying to connect all this together and something we would need to work on further. For the specific YouTube connection, it recognizes when the user is on a YouTube domain and reads if there is an ID to match from the database (which is currently not fully connected) - it loads it if it exists and if not it creates a new file with that ID name and new time stamps based on the community curation, it either mutes or forwards specific time stamps in the video. This initial list will provide us with an extensive database to utilize for our future build that will utilize Machine Learning and through image processing and voice recognition will automatically mute and forward specific scenes with minimal community curation to expand quicker.

Challenges we ran into

We didn’t have anybody proficient in backend development so we struggled with MongoDB Atlas to try and connect our solution into the cloud.

Accomplishments that we're proud of

The front end looks really professional and the UI is accessible. (We also got second in cup stacking and have high hopes for the scavenger hunt)

What we learned

Learning new languages and new libraries well enough for a functional hack is really hard in the midst of the hackathon. We should have formed our team more strategically to benefit all of us with a backend developer instead of all front end developers. However, we still got a working solution and all of us as a group learned how to properly use GitHub and collaborate with each other effectively while having a better understanding of mangoDB and Node.JS. We would love to continue this project by learning more on back-end development to try and make it more robust to enhance our current solution.

What's next for FOULSTOP.

We want to develop the database and link it to MongoDB atlas. We would like to develop it into a more robust platform to ensure it works seamlessly across all videos on YouTube and have a large database curated by the community. Once we have a large dataset, we would also implement image and voice recognition and process our large dataset into a machine learning algorithm so we can transition from a platform that is fully curated by the community to one that is curated by an AI with the help of the community. Once we have that, we would like to add support to other platforms such as Netflix.