AI powered Attendance System (Paperback)

Srinivasan T.

ISBN 10: 6209641237 / ISBN 13: 9786209641237

Published by LAP Lambert Academic Publishing, 2026

About this Item

Paperback. This project presents an AI-based attendance management system developed to modernize and simplify conventional attendance practices through automated, contactless facial recognition. The system uses a Raspberry Pi 4 integrated with a webcam to identify individuals by applying computer vision and machine learning techniques, ensuring reliable and efficient attendance capture.A robust backend developed using Node.js, Express, and Socket.IO enables real-time data synchronization, secure record management, and instant notifications for users and administrators. When an absence is identified, the system requests the individual to submit a reason via a user-friendly web interface, ensuring accountability and transparent documentation. Real-time alerts are generated to inform administrators of irregular or unexpected absences, enabling prompt and effective action.The system also provides detailed analytics and reporting features to analyze attendance patterns and trends. By minimizing manual intervention and reducing human errors, this solution delivers a scalable, intelligent, and data-driven alternative to traditional attendance systems, making it well suited for educational. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9786209641237

Bibliographic Details

• Title: AI powered Attendance System (Paperback)
• Publisher: LAP Lambert Academic Publishing
• Publication Date: 2026
• Language: English
• ISBN 10: 6209641237
• ISBN 13: 9786209641237
• Binding: Paperback
• Condition: new

About this title

Synopsis

This project presents an AI-based attendance management system developed to modernize and simplify conventional attendance practices through automated, contactless facial recognition. The system uses a Raspberry Pi 4 integrated with a webcam to identify individuals by applying computer vision and machine learning techniques, ensuring reliable and efficient attendance capture.A robust backend developed using Node.js, Express, and Socket.IO enables real-time data synchronization, secure record management, and instant notifications for users and administrators. When an absence is identified, the system requests the individual to submit a reason via a user-friendly web interface, ensuring accountability and transparent documentation. Real-time alerts are generated to inform administrators of irregular or unexpected absences, enabling prompt and effective action.The system also provides detailed analytics and reporting features to analyze attendance patterns and trends. By minimizing manual intervention and reducing human errors, this solution delivers a scalable, intelligent, and data-driven alternative to traditional attendance systems, making it well suited for educational.