We are living in a world where everything is automated and linked online. The internet of things, image processing, and machine learning are evolving day by day. Many systems have been completely changed due to this evolve to achieve more accurate results. The attendance system is a typical example of this transition, starting from the traditional signature on a paper sheet to face recognition. We offer your organization a comprehensive embedded attendance system using facial recognition with controlling the door access. If the employee's input image matches with the trained dataset image the prototype door will open, then the attendance results will be stored in the MySQL database. The database is connected to the Attendance Management System (AMS) web server, which makes the attendance results reachable to any online connected web browser.
Facial Recognition and Video Analytics
Video analytics can transform standard CCTV systems into intelligent and effective detection and alert systems. CCTV technology is now capable of recognizing the faces of people, vehicles, animals, and bags automatically.
Integrated with CCTV video analytics, both facial and general recognition software systems are capable of counting, measuring speed and monitoring direction. For example, recognition systems can monitor the duration of time that people are present in a specific area. Moreover, intelligent video analytics software can recognize different behaviors and create an alarm on a user-defined rule.
We help you install facial recognition technology in your classrooms to monitor students’ behavior. In the same way, those cameras could be used to identify students and record their attendance in a class. With photos submitted to schools for various forms and documents, the students’ faces could be added to data sets to record their attendance in the respective classes.
We implement algorithms for face detection and recognition in image processing to build a system that will detect and recognize the frontal faces of students in a classroom. The proposed solution is to develop a working prototype of a system that will facilitate class control for lecturers in a classroom by detecting the frontal faces of students from a picture taken in a classroom.
In Face Detection and Recognition systems, the flow process starts by being able to detect and recognize frontal faces from an input device i.e. mobile phone. In today’s world, it has been proven that students engage better during lectures only when there is effective classroom control. The need for high-level student engagement is very important. In the same way, students need to be continuously engaged during lectures and one of the ways is to recognize and address them by their names. Therefore, a system like this will improve classroom control.