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.
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Librería: California Books, Miami, FL, Estados Unidos de America
Condición: New. Nº de ref. del artículo: I-9786209641237
Cantidad disponible: Más de 20 disponibles
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L0-9786209641237
Cantidad disponible: Más de 20 disponibles
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L0-9786209641237
Cantidad disponible: Más de 20 disponibles
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 52 pp. Englisch. Nº de ref. del artículo: 9786209641237
Cantidad disponible: 2 disponibles
Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: new. 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. Nº de ref. del artículo: 9786209641237
Cantidad disponible: 1 disponibles
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch. Nº de ref. del artículo: 9786209641237
Cantidad disponible: 1 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9786209641237
Cantidad disponible: 2 disponibles
Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. AI powered Attendance System | AI-Driven Attendance Management System with Real-Time Alerts and Absence Logging | Srinivasan T (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209641237 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Nº de ref. del artículo: 134809905
Cantidad disponible: 5 disponibles