Advanced Attendance Checking System with AI Camera - Case study: Co May Dormitory

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By TNI Tech

Jan 03, 2025

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1. About the Customer

Co May dormitory is a charity organization run by the Co May Group, one of Vietnam South's largest agricultural product exporters. Founded with a mission to provide free housing for excellent students, Co May dormitory aims to foster a safe, secure, and convenient living environment that supports academic excellence and personal growth. With hundreds of students living on-site, ensuring effective management and safety has been a top priority for the organization.

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2. About the Project

  • Industry: Education
  • Region: Ho Chi Minh City, Vietnam
  • Time: 2024

As Co May Dormitory expanded its capacity to accommodate more students, the need for a robust and unified security and management system became increasingly apparent. The project aimed to address operational inefficiencies, improve security, and provide a user-friendly experience for dormitory staff and residents.


3. Problems

3.1. Attendance Checking System Challenges

The dormitory previously relied on an RFID-based attendance system. Students were required to carry RFID cards for attendance verification. While this system was functional, it was vulnerable to security loopholes. Students could exploit the system by scanning cards on behalf of their peers, making it difficult to ensure genuine attendance.

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3.2. Disjointed CCTV Management

The dormitory’s existing CCTV infrastructure consisted of cameras from different manufacturers, including Hikvision, Dahua, and Imou. Each brand required a separate app for camera monitoring, which complicated user experience and operational efficiency. Staff struggled to manage multiple interfaces, leading to delays in incident response and system management.

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3.3. Security Threats

Despite the presence of a CCTV system, theft incidents during nighttime persisted. Thieves occasionally scaled fences to intrude on the premises and steal valuable assets. The existing system lacked advanced analytics capabilities, such as intrusion detection, to proactively identify and prevent unauthorized access.

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4. Solutions

To address these issues, an all-in-one AI-enabled software solution was developed and deployed. The system was tailored to meet the dormitory's unique needs, combining advanced video management capabilities with AI-powered analytics.

4.1. Unified Video Management System (VMS)

The software integrates seamlessly with 99.9% of commercially available camera brands, including the dormitory’s existing Hikvision, Dahua, and Imou cameras. This VMS provides a centralized platform for live viewing, recording, playback, and camera configuration. Staff now have a unified user interface, eliminating the need for multiple apps and enhancing operational efficiency.

4.2. AI-Powered Video Analytics

4.2.1. Face Recognition for Attendance

The attendance system was upgraded to utilize AI-enabled face recognition technology. The system ensures that attendance is only marked when the AI camera identifies the actual individual. This eliminates the possibility of fraudulent attendance practices, making the process more transparent and reliable.

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4.2.2. Intrusion Detection

The solution includes an AI-powered intrusion detection module. It detects unauthorized activities, such as individuals climbing over fences, and sends real-time alerts to the dormitory staff. All incidents are recorded, providing valuable evidence for further investigation and enhancing overall security.

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5. Result

The deployment of the AI camera system brought significant improvements to Co May Dormitory’s operations:

5.1. Streamlined Camera Management

The unified VMS platform allowed the dormitory staff to manage all cameras - existing and new - within a single interface. Key features such as live view, recording, and configuration were easily accessible, reducing complexity and improving response times.

5.2. Transparent Attendance Checking

The new attendance system enhanced security and accountability. By leveraging AI-based face recognition, attendance records became accurate and tamper-proof, fostering trust among students and staff.

5.3. Enhanced Security

Intrusion detection capabilities significantly reduced theft incidents. Real-time notifications enabled staff to respond promptly, while recorded footage served as a deterrent for potential intruders. These improvements contributed to a safer living environment for students.


6. Conclusion

The implementation of the AI camera system at Co May Dormitory highlights the transformative potential of modern technology in enhancing security and operational efficiency. By addressing critical challenges such as attendance fraud, fragmented camera management, and security threats, the system has become an integral part of the dormitory’s operations.

This case study underscores the importance of adopting innovative solutions to meet the evolving needs of organizations in the education sector. With its advanced capabilities, the AI camera system not only supports the dormitory’s mission of providing a secure and conducive living environment but also sets a benchmark for similar institutions seeking to modernize their operations.