Development of vicinity monitoring system using face recognition technology/
Alvin P. Bautista, Juliues Patrick Bibay, Rommel John C. Macasukit and Claisse Neriel L. Martinez.--
- Technological University of the Philippines, Manila. 2023
- x, 107 pages. 29cm
Bachelor's thesis
College of Industrial Technology.--
Includes bibliographic references and index.
Security and safety must be one of the top priorities of educational institutions. It is undeniable that as student population increases, crime rate deteriorates with it — posting threat to students’ safety, as well as to faculty members and staff. Such alarming societal issue leads to the development of the vicinity monitoring system to ensure the safety and security of the students and staff. This system also aims to manage the crowding problem
on the 4th floor CIT-Building Electronics Engineering Technology Department of TUP- Manila. The system uses face recognition technology to recognize and to identify the
person that enters and exits the vicinity; and generates a time log when the person is identified. It is also designed to display the number of detected registered students and staff. An alarm was built into the system that will be triggered once the system detects an unregistered facial feature. A report will be generated with the number and frequency of unregistered face detected. The system uses a classifier model, to detect and recognize faces. For the project development, the researchers used Java and an IDE specified for Java Projects called NetBeans and MySQL as the database. It also uses a server-client setup wherein a 1080p full-HD Web Camera will be installed in a client laptop. This will act as the input and the sender, while the other laptop will act as the server. Based on gathered results, the user purpose and stated task are encompassed by the set of functions used in the system. Each module operated rendering to the condition desired in the system. This signifies that the system is user-friendly and can be operated from time to time. The system was evaluated by 21 evaluators composed of Information Technology professors, staffs and students of 4th floor CIT-Building Electronics Engineering Technology Department of TUP-Manila using ISO 25010 software quality model and was rated with a mean rating of 4.33 which is considered as “Very Good”, which means it’s a reliable tool for monitoring vicinities.
Information Technology Face Recognition Technology