The advancement of IoT technology has significantly transformed various domains, including attendance management systems. This paper presents an IoT-based attendance system that incorporates ESP32 CAM for facial recognition and a fingerprint sensor in a portable device, enhanced with a built-in charging mechanism and a custom-made PCB for the circuit. The system leverages machine learning algorithms for facial recognition, facilitating real-time data processing and secure transmission of authenticated attendance records to a server. These records are subsequently synchronized with cloud-based storage and made accessible through a mobile application. By combining facial recognition and fingerprint authentication, the system enhances the accuracy and security of attendance tracking while improving user experience and operational efficiency. The portability of the device allows teachers to easily carry and hand it over to students for seamless attendance collection. Extensive testing showcases the system's robustness, reliability, and adaptability across different environments, highlighting its potential to improve modern attendance management practices.