Finalist Pitch: https://www.youtube.com/watch?v=1AcCg4nhS8g

Hackathon Details: https://codebrew-2024.devpost.com/ + https://codebrew.cissa.org.au/

Video Pitch: https://devpost.com/software/lockedin-yi73xd

Team Members: Anshul Godhani (https://www.linkedin.com/in/agodhani/) | Hannah Luo (https://www.linkedin.com/in/hannah-l-77a806254/) | Leo Wang (https://www.linkedin.com/in/leo-wang-0b68bb273/) | Dorn Kasikumpaiboon (https://www.linkedin.com/in/dornkasikumpaiboon/) |
Surya Sathyamurthy (https://www.linkedin.com/in/surya-sathyamurthy-605722217/) |

Welcome to LockedIn, the next level of study efficiency that employs cutting-edge technology to help you maximize your study sessions. With a focus on real-time engagement tracking through facial recognition, LockedIn is designed to transform how you study, ensuring every minute spent is effective.

Have you ever spent countless hours studying, only to find that you've made little to no progress? Traditional study methods and apps may not always reflect the true efficiency of your sessions. That's where LockedIn comes in, offering a solution to a common problem many students face.

Studying for long hours but achieving minimal progress is a common issue. Existing solutions like the Forest app encourage focus but rely heavily on self-reporting, which doesn't accurately measure the actual time spent focusing.

LockedIn offers a unique approach by combining a minimalist and user-friendly design with advanced facial recognition technology. This provides you with a real-time efficiency metric that truly reflects the time you spend focused on your studies.

• Real-Time Facial Recognition: Utilizes advanced machine learning models to detect your focus direction, ensuring you're engaged with your work.
• Efficiency Tracking: Automatically calculates the time you spend focused, providing a running efficiency percentage.
• Session Recording: Enables the recording of study sessions for later review, helping you identify and improve your study habits.
• Minimalist Design: Designed for ease of use, with clearly distinguishable features and progress tracking to encourage frequent and prolonged use.
• Privacy-Focused: Operates entirely offline, ensuring your data remains secure and inaccessible to any third parties.

1. Start a Study Session: Press start, and the app begins tracking your focus using facial recognition.
2. Focus Detection: Detects when you're looking at the screen and calculates your focus time.
3. Review and Improve: Review your efficiency metrics and recorded footage to identify areas for improvement.
4. Pause and Reset: Allows you to take short breaks and reset the timer as needed.
5. Time Log: Records the time you spend studying and your efficiency metrics.
6. Export Time Log to CSV: Enables exporting your time log for further analysis or sharing.

1. Clone this repository.
2. Open the Log_Timer.html file in Visual Studio Code and run it using the Live Server extension.
3. Allow camera access to enable real-time facial recognition.
4. Upload and replace the PNG file in the user folder in the FaceRec folder. This picture will be used for facial recognition. Each user only needs to upload one straight-face PNG file.
5. Start improving your study efficiency today!

We've opted for a minimalist design to make the app as intuitive and easy to use as possible, ensuring quick comprehension and effective use.

The chart display feature is currently a proof of concept and is not fully implemented. If you would like to try the non-camera mode, please run "homePage.html"

Your privacy is our top priority. LockedIn operates entirely offline, ensuring your data is secure and inaccessible to external parties.

We welcome contributions! If you have suggestions for improvements or new features, please feel free to submit an issue or pull request.

LockedIn is open-source software licensed under the MIT license.

Transform your study sessions into productive achievements with LockedIn, where efficiency meets privacy.