An AI-Powered Academic Assistant for Automated Attendance and Voice-Based Student Support Using Raspberry Pi

This paper presents the design and development of an AI-powered academic assistant aimed at automating student attendance and providing intelligent voice-based academic support. The system is built using a Raspberry Pi 4 Model B (8GB), integrated with a Raspberry Pi Camera Module v2 NOIR, USB microphone, and speaker, offering a cost-effective, standalone solution for educational institutions. Utilizing OpenCV, the system performs real-time facial recognition to record both in-time and out-time attendance, thereby increasing accuracy and accountability. Attendance tracking is limited to predefined time periods to optimize system efficiency. In parallel, the assistant features a voice-interactive chatbot, developed using Python libraries such as speech_recognition and pyttsx3, enabling students to receive spoken responses to academic queries. A Flask-based web application allows mentors to manage attendance records and set student-specific reminders through an intuitive dashboard. Data is handled using lightweight JSON-based storage, ensuring offline operability and privacy without reliance on cloud services. The entire system operates effectively under a budget of ₹13,000, making it highly suitable for deployment in rural or resource-constrained educational environments. The integration of AI, voice interaction, and edge computing creates a scalable, modular tool that enhances the educational experience for both students and mentors. This work demonstrates how embedded AI systems can bring intelligent automation into the classroom, and lays the foundation for future developments such as NLP-based chatbots, multi-language support, and integration with institutional databases.