Gurukul AI Tech

Inspiration

•Educational institutions face challenges in managing attendance, student engagement, library operations, and hostel security.

•Traditional methods are often time-consuming, error-prone, and require manual supervision, leading to inefficiencies.

• A lack of automation in these fields further impacts accuracy, security, and overall effectiveness.

What it does

The proposed prototype leverages AI to take Attendance in classes and seminars, Manage Library Books, and Hostel Surveillance.

All of these features on a Smartphone which links to the college database and uses latest ML models for face recognition, image analysis, etc.

How we built it

Step 1 - Figure out a roadmap Step 2 - Research about AI models Step 3 - Finetune the models Step 4 - Import in JSON and write the code Step 5 - Deployed

Challenges we ran into

Features like hand tracking, book recognition, and facial expression analysis are hard to implement and I am still trying to implement them in my code.

Accomplishments that we're proud of

Running deep learning models efficiently on phones is a hard technical challenge and we’re almost there!

Scalable for different industries – can be expanded for office attendance, conference tracking, or interactive training sessions.

What we learned

I learnt about zero shot classification, Various AI models and implementation of AI based solutions on real life problems.

What's next for Gurukul AI Tech

Planning to implement YOLOv8, FaceNet and other dbms techniques so that I can link it with University infrastructure to scale it and make the system more efficient.

Built With

• react
• tensorflow
• vercel