The business requirement for the Smart Facial Recognition Attendance System emerged from the need to modernize and streamline the recruitment process of Nepal Police, particularly during large-scale physical examinations. Traditional manual attendance methods were time-consuming, prone to errors, and lacked transparency. The department required a secure, efficient, and contactless solution to accurately identify and record the presence of recruits in real time. Additionally, they needed a centralized web-based platform to manage and monitor attendance data remotely. This led to the development of a system that leverages facial recognition technology, embedded systems (Orange Pi), and web-based tools to ensure reliability, speed, and operational efficiency in a mission-critical environment.

To address the identified needs, Tech Nirvana, in collaboration with Zener Technologies, developed a comprehensive Smart Facial Recognition Attendance System tailored for the Nepal Police recruitment process. The solution included a Linux-based facial recognition application deployed on Orange Pi, capable of capturing and verifying recruits' faces in real time using Python, dlib, and machine learning algorithms. Complementing this, a secure web-based dashboard was built to allow authorized personnel to remotely view, manage, and update attendance records. This integrated system provided a contactless, efficient, and accurate method of tracking attendance during physical exams, significantly reducing manual work and enhancing transparency and data reliability.