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{ "item_title" : "AI powered Attendance System", "item_author" : [" Srinivasan T", "Yokesvaran K "], "item_description" : "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.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/6/20/964/123/6209641237_b.jpg", "price_data" : { "retail_price" : "50.00", "online_price" : "50.00", "our_price" : "50.00", "club_price" : "50.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
AI powered Attendance System|Srinivasan T

AI powered Attendance System

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Overview

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 Non-Returnable

Details

  • ISBN-13: 9786209641237
  • ISBN-10: 6209641237
  • Publisher: LAP Lambert Academic Publishing
  • Publish Date: February 2026
  • Dimensions: 9 x 6 x 0.12 inches
  • Shipping Weight: 0.18 pounds
  • Page Count: 52

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