International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Mess Monitoring and Billing System Using Raspberry Pi |
|---|---|
| ABSTRACT | The research paper "Mess Monitoring and Billing System Using Facial Recognition and Raspberry Pi" presents an automated system to address inefficiencies in college mess operations, such as proxy entries and manual billing. It uses Raspberry Pi 4 for real-time facial recognition, attendance logging, and instant deductions from student balances during meal slots, with email notifications for transparency. The system includes a web-based admin panel for student registration with facial datasets, OpenCV for face detection, and MySQL for storing attendance, billing, and unknown face logs. Unauthorized entries are flagged and recorded for security, eliminating manual processes and reducing errors. System Benefits Deployment on low-cost edge hardware ensures scalability, contactless operation, and real-time monitoring suitable for institutions. It prevents fraud, cuts queues, and provides audit-ready reports, outperforming traditional ID or token methods. |
| AUTHOR | PRASANNA KUMAR M, AMIT S NAVI, ANUSHA HALAPPANAVR, CHETHANA S, PALLAVI M Associate Professor, Dept. of EIE, Dr. Ambedkar Institute of Technology, Karnataka, India Students, Dept. of EIE, Dr. Ambedkar Institute of Technology, Karnataka, India |
| VOLUME | 177 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1312131 |
| pdf/131_Mess Monitoring and Billing System Using Raspberry Pi.pdf | |
| KEYWORDS | |
| References | 1. Face Recognition Based Attendance System - Benazir Begum A et al., IJTSRD, 2021[1] 2. IoT-Based Smart Classroom for Monitoring Students Attendance Using Face Recognition – K. Taha et al., ICCAIS, 2020[1] 3. An Efficient Face Recognition-Based Attendance System for Universities Using Machine Learning and IoT - M. Keshari et al., SPIN, 2021[1] 4. Artificial Intelligence for Student Assessment: A Systematic Review - Gonzlez-Cal atayud V et al., Applied Sciences, 2021[1] 5. Enhancing University Security: A Machine Learning and IoT Driven Face Recognition System - Various Authors, ResearchGate, 2021[1] |
