<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The increase in Internet of Things (IoT) technologies for security in higher vocational institutions provides new solutions to enhance campus security. The challenges faced by campus security management include break-ins, emergency response, and environmental monitoring. Effective security system design can improve the ability to deal with these challenges and ensure the safety and comfort of students and faculty. In this study, an intelligent security system based on IoT technology is designed to realize dynamic management and real-time response to campus security by integrating advanced face recognition, environmental monitoring and data analysis technologies, thus improving campus security and management efficiency. Haar feature recognition, face detection optimized by Adaboost algorithm, and ecological monitoring technologies are some of the technological approaches introduced in the study. The system design integrates multiple aspects such as video surveillance, environmental parameter monitoring, and data analysis to build an efficient and reliable security monitoring system. In this paper, the system can monitor the campus security situation in real time, the face recognition accuracy rate reaches 95%, and the illegal intrusion detection time is reduced to within 2 seconds, effectively improving the response speed and accuracy of campus security management. This study proves the effectiveness and feasibility of IoT technology in designing campus intelligent security systems, which is of great significance to improve campus security management.</p>
</abstract>

The increase in Internet of Things (IoT) technologies for security in higher vocational institutions provides new solutions to enhance campus security. The challenges faced by campus security management include break-ins, emergency response, and environmental monitoring. Effective security system design can improve the ability to deal with these challenges and ensure the safety and comfort of students and faculty. In this study, an intelligent security system based on IoT technology is designed to realize dynamic management and real-time response to campus security by integrating advanced face recognition, environmental monitoring and data analysis technologies, thus improving campus security and management efficiency. Haar feature recognition, face detection optimized by Adaboost algorithm, and ecological monitoring technologies are some of the technological approaches introduced in the study. The system design integrates multiple aspects such as video surveillance, environmental parameter monitoring, and data analysis to build an efficient and reliable security monitoring system. In this paper, the system can monitor the campus security situation in real time, the face recognition accuracy rate reaches 95%, and the illegal intrusion detection time is reduced to within 2 seconds, effectively improving the response speed and accuracy of campus security management. This study proves the effectiveness and feasibility of IoT technology in designing campus intelligent security systems, which is of great significance to improve campus security management.

Design of Intelligent Security System for Higher Vocational Colleges Based on Internet of Things

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

The increase in Internet of Things (IoT) technologies for security in higher vocational institutions provides new solutions to enhance campus security. The...

Design of Intelligent Security System for Higher Vocational Colleges Based on Internet of Things

Publicado en línea: 03 may 2024

Páginas: -

Recibido: 05 abr 2024

Aceptado: 17 abr 2024

DOI: https://doi.org/10.2478/amns-2024-0876

Palabras clave
Internet of things, Intelligent security system, Face recognition, Environmental monitoring

© 2024 Ying Wei et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Design of Intelligent Security System for Higher Vocational Colleges Based on Internet of Things

Publicado en línea: 03 may 2024

Páginas: -

Recibido: 05 abr 2024

Aceptado: 17 abr 2024

DOI: https://doi.org/10.2478/amns-2024-0876

Palabras claveInternet of things, Intelligent security system, Face recognition, Environmental monitoring

© 2024 Ying Wei et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
Internet of things, Intelligent security system, Face recognition, Environmental monitoring