S O F T WA RE R E Q U I RE M E N T S S PE C I FI C AT I O N Insecure and Inefficient Traditional Attendance Management System Version 1.0 Feb 18, 2026 Insecure and Inefficient Traditional Attendance Management System Table of Contents 1. Introduction 1.1 Purpose 1.2 Scope 1.3 References 1.4 Overview 2. The Overall Description 2.1 Product Perspective 2.2 Product Functions 2.3 User Characteristics 2.4 Constraints 2.5 Assumptions and Dependencies 3. External interface Requirements 3.1 User Interfaces 3.2 Hardware Interfaces 3.3 Software Interfaces 3.4 Communications Interfaces 4 Tables, Diagrams and Flowcharts 4.1 System Architecture Diagram 4.2 Data Flow Diagram Level -0 4.3 Flowchart of System 3.4 ER diagrams 1. Introduction In educational institutions, attendance management plays a crucial role in maintaining academic discipline and monitoring student participation. Traditionally, attendance is recorded manually by faculty members during lectures, which consumes significant class time and increases administrative workload. Moreover, conventional attendance methods are highly susceptible to proxy attendance and human errors, resulting in inaccurate and unreliable records. With the advancement of computer vision and artificial intelligence technologies, automated systems have emerged as effective solutions to real-world problems. Face recognition technology, a branch of artificial intelligence and image processing, enables the identification and verification of individuals based on their facial features. By leveraging this technology, attendance management can be transformed into a secure, efficient, and automated process. This project proposes a Secure Automated Attendance Management System based on face recognition. The system utilizes existing classroom CCTV infrastructure to detect and verify student presence in real time. By implementing time-based, teacher-controlled attendance sessions, the system ensures controlled access and prevents unauthorized or proxy attendance. The automated mechanism reduces faculty workload, minimizes lecture time wastage, and maintains accurate and verified attendance records. The proposed solution aims to provide a cost-effective, reliable, and practical approach to modernizing attendance systems in educational institutions while enhancing security and operational efficiency. 1.1 Purpose The purpose of this project is to develop a secure, intelligent, and automated attendance management system using face recognition technology. The system is designed with the following key purposes: · To eliminate traditional manual attendance methods o Reduce dependency on paper-based or manual roll-call systems. o Minimize human errors in attendance recording. · To prevent proxy attendance o Verify the actual presence of students using facial recognition. o Ensure authenticity and reliability of attendance records. · To automate the attendance marking process o Save valuable lecture time. o Reduce administrative workload for faculty members. · To utilize existing CCTV infrastructure o Make the system cost-effective and practical for institutions. o Avoid additional hardware installation expenses. · To implement time-based, teacher-controlled attendance sessions o Allow attendance marking only within authorized time windows. o Ensure controlled access and enhanced system security. · To maintain accurate and verified digital records o Store attendance data securely in a database. o Enable easy retrieval and monitoring of attendance reports. Overall, the purpose of this project is to provide a smart, reliable, and technology-driven solution that enhances efficiency, transparency, and security in academic attendance management systems 1.2 Scope The scope of this project defines the boundaries, applicability, and future potential of the proposed Secure Automated Attendance Management System. The scope includes the following aspects: 1. Implementation in Educational Institutions a. Applicable for schools, colleges, and universities. b. Can be used in classrooms equipped with CCTV cameras. 2. Real-Time Face Recognition-Based Attendance a. Detect and recognize students during live classroom sessions. b. Automatically mark attendance based on verified facial identity. 3. Teacher-Controlled Attendance Sessions a. Attendance can only be marked within a predefined time window. b. Faculty members can initiate and terminate attendance sessions. 4. Database Management and Record Maintenance a. Store attendance data securely in a digital database. b. Generate attendance reports for monitoring and analysis. 5. Cost-Effective Deployment a. Utilizes existing CCTV infrastructure. b. Minimizes additional hardware requirements. 6. Scalability and Future Expansion a. Can be extended to include multi-class and multi-department integration. b. Future enhancements may include cloud storage, mobile app integration, and advanced analytics dashboards. 7. Security and Authentication a. Prevent unauthorized access. b. Ensure data privacy and integrity. Scope Limitation: · System performance may depend on camera quality and lighting conditions. · Initial dataset collection of student facial data is required 1.3 References · P. Viola and M. Jones, “Rapid Object Detection using a Boosted Cascade of Simple Features,” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) , 2001. · I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning , MIT Press, 2016. · R. Szeliski, Computer Vision: Algorithms and Applications , Springer, 2010. · OpenCV Documentation, “Face Detection and Recognition,” Available: https://docs.opencv.org · A. Krizhevsky, I. Sutskever, and G. Hinton, “ImageNet Classification with Deep Convolutional Neural Networks,” Advances in Neural Information Processing Systems (NIPS) , 2012. · Python Software Foundation, “Python Documentation,” Available: https://docs.python.org · M. Turk and A. Pentland, “Eigenfaces for Recognition,” Journal of Cognitive Neuroscience , 1991. · Research Article: “Face Recognition Based Attendance System,” International Journal of Engineering Research & Technology (IJERT) , 2019. 1.4 Overview The Secure Automated Attendance Management System is a technology-driven solution designed to modernize the traditional attendance process in educational institutions. The system integrates face recognition technology with real-time video processing to automatically identify and verify student presence during classroom sessions. The system operates by capturing live video feed through existing CCTV cameras installed in classrooms. The captured frames are processed using face detection and recognition algorithms to match student faces with pre-registered data stored in the database. Once a student’s identity is successfully verified within the authorized time window, the system automatically marks attendance in the database. The overall architecture of the system consists of the following main components: · Face Detection Module o Detects human faces from live video frames. · Face Recognition Module o Matches detected faces with stored student facial data. · Database Management System o Stores student details and attendance records securely. · Teacher Control Interface o Allows faculty to start and stop attendance sessions. o Controls time-based access for marking attendance. · Report Generation Module o Generates attendance reports for monitoring and evaluation. The system ensures security by restricting attendance marking to authorized sessions and preventing duplicate or proxy entries. By automating the entire process, it reduces manual effort, saves lecture time, and maintains accurate, reliable, and tamper-resistant attendance records. Overall, this project presents a practical and scalable solution that combines artificial intelligence, computer vision, and database management to enhance efficiency and transparency in academic attendance systems. 2. The Overall Description This section provides a general description of the Secure Automated Attendance Management System. It explains the overall working, system perspective, user characteristics, constraints, and assumptions of the proposed system 2.1 Product Perspective The Secure Automated Attendance Management System is a standalone yet integrable software system designed to automate attendance marking using face recognition technology. · The system integrates with existing classroom CCTV cameras. · It processes real-time video feed to detect and recognize student faces. · It connects with a centralized database to store and manage attendance records. · The system can be integrated with institutional ERP systems in future. The product follows a modular architecture consisting of: · Face Detection Module · Face Recognition Module · Database Management System · Teacher Control Panel · Report Generation System 2.2 Product Functions The major functions of the system include: 1. Capturing live video feed from classroom CCTV cameras. 2. Detecting human faces from video frames. 3. Recognizing and verifying student identities. 4. Automatically marking attendance for verified students. 5. Allowing teachers to start and stop attendance sessions. 6. Preventing duplicate or proxy attendance. 7. Storing attendance records securely in a database. 8. Generating attendance reports for monitoring and evaluation. 2.3 User Characteristics The system is designed for the following users: 1. Faculty Members · Basic knowledge of computer operations. · Ability to operate attendance control panel. · Responsible for initiating attendance sessions. 2. Students · No technical knowledge required. · Must register facial data during initial enrollment. 3. System Administrator · Technical knowledge of system setup. · Responsible for database management and maintenance. · Handles system configuration and updates. 2.4 Constraints The system has the following constraints: 1. Requires good quality CCTV cameras. 2. Performance depends on lighting conditions in classroom. 3. Requires initial facial data registration. 4. Requires stable power supply and system connectivity. 5. Data privacy regulations must be followed. 2.5 Assumptions and Dependencies The system operates under the following assumptions: 1. All students register their facial data before use. 2. CCTV cameras are properly installed and functional. 3. The classroom environment provides sufficient lighting. 4. Database server remains operational. 5. Faculty members operate the system within authorized time. 3.1 External Interface Requirements This section describes how the system interacts with users and external components. 3.1 User Interface Requirements 1. The system shall provide a simple and user-friendly interface. 2. The teacher dashboard shall include: o Start Attendance Session button o Stop Attendance Session button o View Attendance Records option 1. The admin panel shall allow: o Student registration o Face data upload o Database management 1. The interface shall display confirmation after successful attendance marking. 3.2 Hardware Interface Requirements 1. The system shall use classroom CCTV cameras for video input. 2. The system shall require a computer/server to process video frames. 3. Minimum hardware requirements: o Processor: i5 or higher o RAM: 8GB minimum o Camera resolution: 720p or above 3.3 Software Interface Requirements 1. Operating System: Windows / Linux 2. Programming Language: Python 3. Libraries: o OpenCV o NumPy o TensorFlow / Keras o Dlib 1. Database: MySQL / SQLite 3.4 Communication Interface Requirements 1. The system shall communicate with the database server. 2. Secure data transmission protocols shall be used. 3. System may support LAN-based classroom integration. 3.2 Functional Requirements Functional requirements define what the system must do. 1. The system shall detect faces from live CCTV feed. 2. The system shall compare detected faces with stored database images. 3. The system shall mark attendance only for verified matches. 4. The system shall prevent duplicate attendance marking. 5. The system shall allow teachers to control attendance session timing. 6. The system shall store attendance records with date and time stamp. 7. The system shall generate attendance reports. 8. The system shall allow admin to add, update, or remove student data. 3.5 Performance Requirements This section defines the performance expectations of the system. 1. Real-Time Processing a. The system shall process live video feed with minimal delay. b. Face recognition response time should be within 1–3 seconds. 2. Accuracy a. The system shall maintain high face recognition accuracy (minimum 90% under proper lighting conditions). b. False acceptance and false rejection rates should be minimized. 3. System Efficiency a. The system shall support attendance marking for at least 60 students per session. b. The system shall handle multiple sessions per day without performance degradation. 4. Database Performance a. Attendance records shall be stored instantly after verification. b. Report generation should not take more than a few seconds. 5. Reliability a. The system shall operate continuously during lecture hours without crashes. 3.6 Logical Database Requirements This section describes the logical structure of the database used in the system. The system database shall contain the following major entities: · Student Table o Student_ID (Primary Key) o Name o Roll_Number o Department o Face_Data (Encoded format) · Attendance Table o Attendance_ID (Primary Key) o Student_ID (Foreign Key) o Date o Time o Status (Present/Absent) · Faculty Table o Faculty_ID o Name o Subject o Session_Time · Admin Table o Admin_ID o Username o Password The database shall ensure: · Data integrity · Secure storage · Fast retrieval · Proper relationship between tables 3.7 Non-Functional Requirements Non-functional requirements describe system quality attributes. 1. Security Requirements · Only authorized users shall access the system. · Attendance sessions shall be teacher-controlled. · Student facial data shall be securely stored. · Password protection for admin access. 2. Usability Requirements · The system shall provide a simple and easy-to-use interface. · Minimal training shall be required for faculty members. 3. Reliability Requirements · The system shall function properly during lecture hours. · Backup mechanism shall be available for database storage. 4. Maintainability Requirements · The system shall allow easy updates and modifications. · Code structure shall be modular for future enhancements. 5. Scalability Requirements · The system shall support increasing number of students. · It shall be expandable to multiple classrooms and departments. 4. Tables, Diagrams and Flowcharts This section presents the structural and logical representation of the Secure Automated Attendance Management System through tables, diagrams, and flowcharts to provide a clear understanding of system architecture and workflow. 4.1 System Architecture Diagram (Description) The system follows a modular architecture consisting of interconnected components. Main Components: v CCTV Camera Ø Captures live classroom video feed. v Face Detection Module Ø Detects faces from video frames using computer vision algorithms. v Face Recognition Module Ø Matches detected faces with stored facial data. v Database Server Ø Stores student information and attendance records. v Teacher Control Panel Ø Allows faculty to start and stop attendance sessions. v Report Generation Module Ø Generates attendance reports. Architecture Flow: 4.2 Data Flow Diagram (DFD) – Level 0 Main Process: · Attendance Management System Data Flow: · Student → Face Image Input · Faculty → Session Control · Admin → Student Data Management · System → Attendance Report 4.3 Flowchart of System Working Step-by-Step Process: 1. Start System 2. Teacher Initiates Attendance Session 3. CCTV Captures Video Feed 4. System Detects Faces 5. Face Recognition Process 6. Match Found? o Yes → Mark Attendance o No → Ignore 1. Store Record in Database 2. Generate Report 3. End Session 4.4 ER Diagram Description The Entity Relationship (ER) diagram includes: Entities: · Student · Attendance · Faculty · Admin Relationships: · One Student → Many Attendance Records · One Faculty → Many Sessions · Admin → Manages Students Primary and foreign keys ensure relational integrity.