Inspiration 💡
The advance in technology, especially with artificial intelligence and machine learning, has brought dramatic changes to improving healthcare. Our team wanted to tackle issues . We also wanted to introduce a product that many students hackers could find useful. This is how we came up with "Blinkr", a blink counting program to prevent eyestrain.
What it does 🧐
Once you access the page, your webcam will detect your face and count how many times you blink your eyes in a minute while you are on your computer. If your blink count drops below the recommended blink frequency, which is 10 to 20 per minute, the page will send a notification to remind you to start blinking more.
How we built it 🛠️
We imported the Face detection ML model library and applied the ear aspect ratio (EAR) model, which is a mathematical model used for determining whether one's eyes are closed. If your eye-blinking rate is under the recommended level, Blinkr will send you notification via webpage.
Challenges we ran into 🤯
Integrating the ML model library and researching how to detect whether one's eyes are closed were some of the biggest challenges we ran into. Everyone was also relatively unfamiliar with writing code in JavaScript and HTML, so we had to basically learn and write code simultaneously.
Accomplishments that we're proud of 💪
We have successfully created a chrome extension, which was the team's primary objective for this hackathon.
What we learned 📚
We have learned to familiarize ourselves with new programming languages, frameworks, tools and software development methodologies in a limited span of time.
What's next for Blinkr: Smart Eye Protection 🏃♀️
We plan to improve the design by upgrading the notification to a banner notification. We are also considering adding a dashboard that tracks our blink count according to the activity category (e.g. watching videos, writing a document, etc.).
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