RESPOGUARD: development of an anomaly detection system for real-time surveillance in Barangay 294 Binondo, Manila using machine learning/
Jayogue, Justin Lawrence C.
RESPOGUARD: development of an anomaly detection system for real-time surveillance in Barangay 294 Binondo, Manila using machine learning/ Justine Lawrence C. Jayoque, Marc Samuel R. Medina, Christian James Pallar, John Paul F. Pasion, and Mark Joseph Emmanuelle A. Venales - Manila: Technological University of the Philippines , 2024. - x,91pages: 29cm. +1 CD-ROM (3/4in.)
Thesis (undergraduate)
College of Science--
Includes bibliography.
Respoguard is an anomaly detection system that combines CCTV technology and machine
learning algorithms for real-time monitoring in Barangay 294 in Binondo, Manila. CCTV and
machine learning work together to promote proactive monitoring and early anomaly identification,
both of which are essential for improving community safety. The researchers developed a web
application that allows for the immediately accurate reporting of abnormalities to barangay
officials. The system's major programming language is Python, and its user interface is built with
Vue.js to give a simple interface for live video surveillance and comprehensive report generation
features. The user interface included quick registration, simple dashboard navigation, and access
to a variety of services like notifications, camera views, and system customizations. Using the ISO
25010 to rate. 30 respondents evaluated the system including ten (10) IT Professionals, ten (10)
Barangay officials, and ten (10) Barangay citizens. It has a rating of 3.76 for Functionality, that is
Highly Acceptable, and 3.55 for Performance, Usability, and Efficiency, which is also Highly
Acceptable. The rating for maintainability, portability, and design is 3.63, which is highly
acceptable.
Machine learning
Artificial intelligence
CCTV technology
BTH QA 76 / J39 2024
RESPOGUARD: development of an anomaly detection system for real-time surveillance in Barangay 294 Binondo, Manila using machine learning/ Justine Lawrence C. Jayoque, Marc Samuel R. Medina, Christian James Pallar, John Paul F. Pasion, and Mark Joseph Emmanuelle A. Venales - Manila: Technological University of the Philippines , 2024. - x,91pages: 29cm. +1 CD-ROM (3/4in.)
Thesis (undergraduate)
College of Science--
Includes bibliography.
Respoguard is an anomaly detection system that combines CCTV technology and machine
learning algorithms for real-time monitoring in Barangay 294 in Binondo, Manila. CCTV and
machine learning work together to promote proactive monitoring and early anomaly identification,
both of which are essential for improving community safety. The researchers developed a web
application that allows for the immediately accurate reporting of abnormalities to barangay
officials. The system's major programming language is Python, and its user interface is built with
Vue.js to give a simple interface for live video surveillance and comprehensive report generation
features. The user interface included quick registration, simple dashboard navigation, and access
to a variety of services like notifications, camera views, and system customizations. Using the ISO
25010 to rate. 30 respondents evaluated the system including ten (10) IT Professionals, ten (10)
Barangay officials, and ten (10) Barangay citizens. It has a rating of 3.76 for Functionality, that is
Highly Acceptable, and 3.55 for Performance, Usability, and Efficiency, which is also Highly
Acceptable. The rating for maintainability, portability, and design is 3.63, which is highly
acceptable.
Machine learning
Artificial intelligence
CCTV technology
BTH QA 76 / J39 2024