A faculty researcher from National University (NU) Fairview has developed an artificial intelligence (AI)-assisted security system designed to turn existing campus CCTV networks into proactive monitoring tools for educational institutions.
Independently developed by Herminiño C. Lagunzad, an Information Technology faculty member and Research Coordinator at NU Fairview’s School of Engineering and Technology, the AI-assisted school security and multi-CCTV face identification system aims to strengthen campus situational awareness, incident documentation, and digital evidence preservation.
The working prototype enables security teams to monitor multiple camera feeds simultaneously through key technical features, which include facial identification and verification, restricted-area and after-hours monitoring, multi-frame verification to reduce false positives, and long-distance, low-light processing capabilities.
In the event of a security breach or panic trigger, the system automatically logs the incident, captures screenshots, and archives video recordings for administrative review and evidence retention.
The solution comes amid growing concerns over campus safety following a series of high-profile security incidents across Philippine schools in mid-2026, including violent events in Tacloban City, Las Piñas, and Zamboanga City.
“These incidents demonstrate that school-safety systems must be capable not only of identifying unauthorized persons but also of supporting rapid incident detection, documentation, evidence preservation, and human decision-making when an emergency involves someone who may already have legitimate access to the campus,” Mr. Lagunzad said.
“I believe the project may provide a timely Philippine perspective on how artificial intelligence, computer vision, and existing CCTV infrastructure can be responsibly applied to campus safety.”
Addressing potential ethical and privacy concerns around AI surveillance, Mr. Lagunzad emphasized that the platform is designed to complement — not replace — human security personnel, faculty, and standard emergency protocols.
Moreover, he stressed that the system does not predict criminal behavior or automatically categorize individuals as security threats. Individuals who cannot be matched against an authorized reference database are categorized simply as “UNKNOWN,” signaling security personnel to conduct human verification.
Mr. Lagunzad hopes his contribution may serve to further ongoing public discussion on responsible technology innovation and improving school safety in the Philippines.
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NU researcher develops AI-driven CCTV system to boost campus safety
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