From Surveillance to Trust: Rethinking AI-Powered Attendance in Higher Education

AI Hunters

Sidmanegdé Kayoulou Josée Manuella OUEDRAOGO, Saleh Bichara ABAKAR,Papa Ibrahima SAMB,Mouhamadou Moustapha FALL, Sidi Ahmed Tidjane SARR, Ecole Supérieure Multinationale des Télécommunications

Training / education / pedagogy

Our team is developing an automated attendance system powered by Amazon Rekognition to replace inefficient manual roll calls in higher education institutions. Traditional methods, such as passing around sign-in sheets, result in a significant loss of time for both faculty and students. Our AI-driven solution addresses this issue by capturing classroom images or video streams, detecting individual faces, and matching them against a pre-registered student database. Once a match is confirmed, the system automatically records the student as “Present” in the university’s digital attendance system, ensuring both accuracy and efficiency.

This situation deserves attention because manual attendance tracking consumes up to 10% of lecture time and remains vulnerable to “proxy signing” fraud. Automating this process allows institutions to reclaim valuable instructional time while ensuring greater data accuracy and integrity. Beyond efficiency gains, this transformation opens up significant opportunities for the digital modernization of campus management systems. However, the integration of such technologies also introduces important challenges, particularly regarding biometric privacy and the ethical use of surveillance within educational environments. Addressing these concerns is essential to ensure that technological innovation remains fair, transparent, and respectful of individual consent. From an impact perspective, the proposed solution streamlines administrative workflows for faculty and provides institutions with reliable, real-time analytics on student engagement. This enables better decision-making and contributes to improving student success and long-term attendance sustainability.

Our team is motivated to participate in this challenge to bridge the gap between cloud-native AI theory and practical academic application. We aim to better understand the technical challenges of real-time facial recognition, as well as the ethical frameworks required to deploy biometric systems responsibly. Through this experience, we seek to transform a routine administrative burden into a seamless and efficient digital solution that enhances the academic environment. Our objective is to develop strong expertise in full-stack AI integration while critically exploring how automated systems can be designed to achieve both high accuracy and strict compliance with privacy standards within a university ecosystem.

We propose a human-centered AI-powered attendance system that uses facial recognition to automate attendance tracking while ensuring ethical and responsible use. The system captures classroom images or videos, detects faces, and matches them with a pre-registered student database. Once identified, the student is automatically marked as present in a digital system. Beyond automation, our contribution focuses on responsible AI by integrating key principles: - Explicit user consent before data collection - Secure storage and management of biometric data - Transparency in how the system operates - Human oversight, allowing teachers to validate or correct attendance - Measures to reduce algorithmic bias and ensure fairness - Alternative solutions in case of recognition failure For successful implementation, several conditions are required, including institutional approval, clear data governance policies, access to secure cloud infrastructure, reliable hardware, and user awareness. https://main.d3pfa91kl0g5kv.amplifyapp.com Access Information To explore our platform, you can use the following credentials: Username: admin Password: admin123 These credentials will allow you to access the main interface of the system. For administrator access, please use the following credentials: Email: admin@admin.com Password: Admin1234# This account provides full access to administrative features and functionalities of the platform. For teacher access, the default password is: Default Password: Esm@t2026! Teachers can use this default password to log in and access their dedicated features within the system.