Contributor :
Tilak Gupta
Mentor :
Kavita
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 sign-in sheets, are prone to errors, time-consuming, and lack real-time 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 the project was to evaluate and implement open-source facial recognition models to develop a demo application showcasing the reliability of the chosen model for teacher attendance tracking in Indian government schools. It involved research on available open-source facial recognition models, assessing their suitability for the intended use case, and selecting the most appropriate one. The selected model was integrated into a prototype demo application, providing a tangible demonstration of its accuracy and reliability in real-world scenarios.
Contributor :
Tilak Gupta
Mentor :
Kavita
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 sign-in sheets, are prone to errors, time-consuming, and lack real-time 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 the project was to evaluate and implement open-source facial recognition models to develop a demo application showcasing the reliability of the chosen model for teacher attendance tracking in Indian government schools. It involved research on available open-source facial recognition models, assessing their suitability for the intended use case, and selecting the most appropriate one. The selected model was integrated into a prototype demo application, providing a tangible demonstration of its accuracy and reliability in real-world scenarios.
About Contributor
Tilak is an Integrated Dual Degree student at Indian Institute of Technology (BHU), Varanasi. He is an aspiring MLOPs engineer and extremely passionate contributing AI in finance more explicitly. He is finance geek and loves to research on it. Tilak loves to travel and explore new places full of adventure and alhttps://github.com/gupta-tilakways curious to know the unknowns.
Key Impact Takeaways:
The project will impact government schools across India by simplifying the attendance system and significantly reducing time spent on the process.