Tempus-A Facial Recognition Technology in Attendance Monitoring

Melanie M. Reynoso; Ariane M.  Torres

doi:10.52006/main.v3i2.214

Melanie M. Reynoso Carlos Hilado Memorial State College–Alijis Campus, Bacolod City, Philippines https://orcid.org/0000-0003-2273-0365
Ariane M. Torres University of Negros Occidental-Recoletos, Bacolod City, Philippines https://orcid.org/0000-0003-1398-1891

DOI: https://doi.org/10.52006/main.v3i2.214

Keywords: Information Technology, Face Recognition, Raspberry Pi 3, Haar Cascade, Linear Binary Pattern Histogram (LBPH), Internet of Things, React JS Native, Attendance Monitoring, SMS Notification, Bacolod City

Abstract

Attendance monitoring has strategic importance for every organization. It has shifted from utilizing paper-based attendance monitoring to biometrics, radio-frequency identification, Bluetooth and smart technologies, Internet of Things (IoT), cloud computing, or face recognition technology. Tempus is an automated attendance monitoring system that uses face recognition technology for input, real-time IoT capabilities for processing, and portability of mobile platforms for output. It has hardware and software components. The core of the hardware component is Raspberry Pi 3, which serves as a communication medium between the camera sensor and the information system. Tempus uses Haar Cascade for facial detection and Linear Binary Pattern Histogram (LBPH) for facial recognition. The software component is further divided into two: 1) the information system for administrators, an attendance monitoring which allows encoding of data, creating new user accounts, managing schedules, recording attendance, and generating reports; and 2) mobile platform for end-users, the teachers, that is provided for communication and notification purposes only.