attendAI

MainPage
getting the data from the database
taking a image on the mainpage
detecting multiple faces
detecting faces

Inspiration We developed attendAI to transform the traditional and often error-prone attendance tracking methods in universities and workplaces with a modern, AI-powered facial recognition system.

What It Does attendAI automates attendance recording through facial recognition, offering a seamless, efficient, and accurate tracking system. It features a user-friendly dashboard for real-time data and analytics, designed for both small teams and large organizations.

How We Built It Our team combined expertise in AI, machine learning, and software engineering to create attendAI, using Python for the AI backend and modern web technologies for the frontend. The focus was on scalability, privacy, and user experience.

Challenges We tackled challenges in ensuring facial recognition accuracy and maintaining a stable flow of the software, considering how intense running a model can be. We faced some challenges while implementing a stable flow of data from the model to the frontend and vice versa.

Accomplishments We're proud of attendAI's accuracy and its positive impact on administrative efficiency. Overcoming technical and ethical challenges has been a significant achievement. And we were successfully able to build a standalone as well as a web application as well with a proper live database

What We Learned The project enhanced our understanding of AI and machine learning, especially in facial recognition. It underscored the importance of balancing technological innovation and we learned how to implement a running backend with a live database using django

What's Next We plan to expand attendAI's features, explore additional parameters such as spoofing detecting and work on improving the accuracy of the model more by using a bigger database and implement features like light detection and environment detection to improve the accuracy of the model even more and leverage GPU acceleration to improve the working of the model by using libraries such as cuda

Built With

Submitted to

AstonHack9

Created by

I worked on the front-end using html and css which I designed the pages on figma. I populated the database for testing and presentation.

pazara1208 Rahimi
I significantly developed and helped propose the architecture of the systems.

I wrote our Django backend framework, which connects our Front end and our self hosted Postgres server

Designed the Report page which processes the stored data allowing for data analysis opportunities

Lionel Muskwe
I worked on the model making sure it is stable and accurate to take images from the webpage and process it in order to produce viable results. And i made sure the model integrated with the database and the frontendI worked on the backend as well.

Faran Zafar
I worked on designing the flow of the web-pages, and what information they contained. I integrated back-end with front-end to receive, process and display the values from the database and trained-model. Finally did testing and maintenance.

Aghayev Orkhan

Updates

Faran Zafar started this project — Feb 25, 2024 05:50 AM EST

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