About the program

Description Government schools in India often face challenges in accurately recording and monitoring teacher attendance leading to inefficiencies in resource allocation and management Traditional methods of attendance tracking such as manual signin sheets are prone to errors timeconsuming and lack realtime monitoring capabilities Therefore there is a need for an automated reliable and efficient offline solution to streamline the process of teacher attendance management in government schools The objective of this project is to evaluate and implement opensource facial recognition models to develop a demo application showcasing the reliability of the chosen model for teacher attendance tracking in Indian government schools Students will research available opensource facial recognition models assess their suitability for the intended use case and select the most appropriate one The selected model will then be integrated into a prototype demo application providing a tangible demonstration of its accuracy and reliability in realworld scenarios Goals MidPoint Milestone Goals 1.Research on opensource facial recognition model works onlineoffline both 2.Prepare or outsource benchmark dataset and evaluate models on defined criteria 3.Explore and create user registration pipeline to store facial data and landmarks 4.Goals Achieved By Midpoint Milestone 5.Implement efficient face lookup algorithm with confidence scores 6.Create a demo offlineonline application to facilitate user registration and lookup with geo tagging Expected Outcome 1.Functional prototype of the demo application featuring the facial recognition model in offlineonline for teacher facial registrationonboarding attendance capturing with admin support to track and view associated analysis 2.Benchmark report comparing the performance of available opensource facial recognition models against predefined criteria 3.Documentation outlining the integration process system architecture and user guidelines for future reference and maintenance Acceptance Criteria 1.Highly accurate attendance above a 95 threshold capturing solution 2.The application functions in both online and offline environments if applicable 3.Intuitive user interface for easy registration attendance capture and admin support 4.Robust solution with implemented privacy measures to protect teachers facial data and ensure compliance with relevant data protection regulations Implementation Details 1.Use open source libraries 2.Our platform backend is in nodejs but ai solution can be deployed in python with an endpoint to use

Perks

1. Lucrative stipend of INR 1 lakh over a period of 3 months 2. Dedicated 1 on 1 mentorship by industry experts. 3. Hands-on experience to hone your skills 4. Access to bootcamps and expert sessions 5. Potential job extended internship opportunities 6. Opportunity to network with global open-source tech leaders

Who can apply?

Only those candidates can apply who:

1. are from Any,
2. and specialisation from Any,
3. are available for duration of 3 Months
4. have relevant skills and interests

Terms of Engagement

1. 50000 received on completion of midpoint milestone as decided with mentor 2. 50000 received on completion of final milestone as decided with mentor 3. Certificate of completion received on successful completion of internship

Number of openings

1