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@article{194742,
        author = {Darji Vinay Kumar and Gujjurolla Gopal and Arava Naresh and Khalandar s k and Dr K SUVARNA},
        title = {Face detection based attendance system using ESP32 Embedded and Python},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {4831-4835},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194742},
        abstract = {Attendance management is a critical task in educational institutions, and traditional methods such as manual attendance and RFID-based systems are time-consuming, error-prone, and susceptible to proxy attendance. This project presents a Face Detection Based Attendance System using ESP32 Embedded and Python, which automates attendance marking using computer vision techniques. Initially, facial images of authorized students are captured and stored as a dataset. These images are trained using a face recognition algorithm implemented in Python. During real-time operation, a USB web camera scans student faces and compares them with the trained dataset. If a match is found, attendance is marked as present and stored in an Excel sheet with date and time. If a student is absent, an automatic alert message is sent to the parent via GSM. In case of an unauthorized person attempting access, a buzzer alert is activated and warning messages are displayed on an I2C LCD. The proposed system improves accuracy, security, and efficiency in attendance management.},
        keywords = {Face Recognition, Automated Attendance System, ESP32 Embedded System, Computer Vision, GSM Alert Notification},
        month = {March},
        }