Skip to content

A Robust E-Classroom Platform With Lowest Data-Transmission(8kbps) Leveraging on AI for Overcoming the Internet Access Inequity. We Regenerated Teacher's Screen on Student Console With Bare-Minimum Data-Streaming and Client-Side AI Monitoring Students Presence.

License

Notifications You must be signed in to change notification settings

Chelsi-create/classroom-x

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

CLASSROOM-X

"Low-Bandwidth AI Teaching Platform for overcoming internet access inequity"

Problem-Statement

Slow Internet Connections or Limited Access From Homes in Rural/Hilly/Remote Areas Can Contribute to Students Falling Behind Academically During Online-Era in The Prevailing COVID-Setups, According to a New Report From Michigan State University’s Quello Center.

Our-Hack

A Robust E-Classroom Platform With Lowest Data-Transmission Leveraging on AI for Overcoming the Internet Access Inequity Our Approach Was to Take Shortest Path Instead of Fastest Vehicle , So Instead of Direct Streaming We Regenerated Teacher's Screen on Student Console With Bare-Minimum Data-Streaming and Client-Side AI Monitoring Students Presence.

Presentation-Slides

Presentation-Video

Achievement

Able to Operate at 8 Kbps Speed With 28.8 Mb Hourly Data Consumption as Compared to Google Meet With Requirements of 90 Kbps Speed & 324 Mb/hour.

Data-Transmitted

  • PDF -ANNOTATION
    • STATIC : PDF WHILE PAGE LOADS INITIALLY
    • DYNAMIC : PAGE_NO , COORDINATES_ANNOTATION
  • WHITEBOARD
    • DYNAMIC : COORDINATES_ANNOTATION , CLEAR_FLAG
  • AUDIO-CHANNEL
    • DYNAMIC : VOICE_BULB
  • CHAT-ROOM:
    • DYNAMIC : TEXT
  • SYSTEM:
    • DYNAMIC : ROOM_ID , MODE
  • MONITOR-STUDENTS:
    • DYNAMIC : NONE
    • CLIENT-SIDE AI MODEL MONITORS STUDENTS THROUGH WEB-CAM AND ALERTS THE TEACHER ABOUT STUDENT'S PRESENCE.

Technologies Used

  • Backend:
    • Python/Flask
    • Socket.io
  • Frontend:
    • HTML/CSS/JS
    • JQuery/Bootstrap
    • Tensorflow.js
      • BlazeFace
  • Database:
    • MongoDB
  • Deployment:
    • Heroku

Configuration

Create a .env file in the folder.

Note: Make sure that .env file is at the same place where app.py exists.

Then, enter your MONGO_URI there:

MONGO_URI= **Your Mongo URi**

Installation

Install the Dependencies and devDependencies first:

pip install -r requirements.txt
flask run

About

A Robust E-Classroom Platform With Lowest Data-Transmission(8kbps) Leveraging on AI for Overcoming the Internet Access Inequity. We Regenerated Teacher's Screen on Student Console With Bare-Minimum Data-Streaming and Client-Side AI Monitoring Students Presence.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • CSS 44.5%
  • JavaScript 25.5%
  • HTML 22.4%
  • Python 7.6%